Sociodemographic

Demographic

Annual number of births to women aged 15 to 19 per 1 000 women in that age group. Also known as the age-specific fertility rate for women aged 15 to 19.

1 000 births per woman

Rate

Corrected/Predicted

Reducing adolescent fertility and addressing the multiple underlying factors are essential to improving adolescent sexual and reproductive health and social and economic wellbeing. In the literature on gender implications, there is substantial agreement that women who become pregnant and give birth very early in their reproductive life are subject to increased risk of complications or even death during pregnancy and childbirth. Their children are also more vulnerable. Therefore, preventing births in adolescent is an important measure to improve maternal health and reduce infant mortality.

In addition, women who have children at an early age experience reduced opportunities for socioeconomic improvement, particularly because young mothers are unlikely to continue studying and, if they need to work, may find it especially difficult to combine family and work responsibilities.

The adolescent fertility rate also provides indirect evidence on access to relevant health services since young people, particularly single adolescent girls, often experience difficulties in accessing sexual and reproductive health services.

The age-specific adolescent fertility rate is calculated as a ratio. The numerator is the number of live births to women 15 to 19 years of age. The denominator is an estimate of exposure to motherhood for women 15 to 19 years of age.

The value of this indicator comes from United Nations estimates, based on data representing estimated mid-year values, obtained by linear interpolation of the corresponding United Nations five-year medium-variant population projections.

Estimation method for global and regional aggregates:
World Population Prospects (WPP) age-specific fertility rates are calculated according to population reconstruction at the country level and provide a better estimate based on all available demographic information. WPP potentially considers as many types and sources of empirical estimates as possible (including retrospective birth histories, and direct and indirect fertility estimates). Final estimates are derived to ensure the greatest possible internal consistency with all other demographic components and intercensal cohorts listed in successive censuses.

In 2018, the adolescent fertility rate in country A was 20.7 per 1 000 adolescent women. This means that, during that year, there were an estimated 21 births per 1 000 women 15 to 19 years of age.

No disaggregation

The international comparability of this indicator may be affected by the frequency of population censuses and demographic surveys. Population censuses are usually conducted every 10 years and survey frequency varies between different countries, with sampling error also a factor. The value of the indicator also depends on adequate coverage of the civil registry (greater than 90 percent), timely registration of deaths and births in the system, and the integrity of the registry.

The estimated value of this indicator may differ from country statistics due to factors such as methodological differences in developing population estimates and projections.

United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects. Available from:
https://population.un.org/wpp/

Annual

United Nations (UN). Department of Economic and Social Affairs.
Sustainable Development Goals (SDG)
Indicator 3.7.2 Adolescent fertility rate (10-14 years; 15 to 19 years) per 1 000 women in that age group.
Available from: https://unstats.un.org/sdgs/metadata/

Pan American Health Organization. Strategic Plan of the Pan American Health Organization 2020-2025.
Indicator 2.b Fertility rate in women 10-19 years of age (disaggregated by 10-14 and 15-19 years) in Latin America and the Caribbean
Available from: https://www.paho.org/en/documents/paho-strategic-plan-2020-2025

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from:
https://www.who.int/data/gho/data/indicators

United Nations, Department of Economic and Social Affairs, Population Division. Handbook on the Collection of Fertility and Mortality Data. For a complete information on the different calculation methods, see United Nations Publication, No. E.03.XVII.11. Available from: https://unstats.un.org/unsd/publication/seriesf/seriesf_92e.pdf

United Nations. Indirect estimation methods are discussed in Manual X: Manual X: Indirect Techniques for Demographic Estimation, United Nations, N°: E.83.XIII.2. Available from:
https://www.un.org/en/development/desa/population/publications/pdf/mortality/Manual_X.pdf

Mortality

Cause of death

The estimated total number of deaths from Alzheimer disease, vascular dementia, and unspecified dementia in the population, in a given country, territory or geographic area during a specific calendar year, divided by the total number of this population, generally estimated in the middle of the same year (1 July), after removing the effect of differences in the age distribution. Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected

The mortality rate from Alzheimer disease and other dementias is applicable to the design, implementation, and evaluation of health policies related to dementia diseases and the distribution of economic, human, and technological resources for this group of diseases, among others. Its applications include to estimate the specialized health personnel required to address these pathologies.

The age-adjusted Alzheimer disease and other dementias mortality rate allows for the comparison of this indicator across populations or in the same population over time.

The numerator of this indicator uses deaths from Alzheimer disease, vascular dementia, and unspecified dementia from the World Health Organization (WHO) Global Health Estimates (GHE). These estimates are based on data from multiple sources, such as: national civil registry systems, estimates from WHO technical programs, the United Nations and inter-agency groups, and the Global Burden of Disease, among others.

The underlying causes of death correspond to codes F01 - F03, G30 - G31 of the International Classification of Diseases, Tenth Revision (ICD-10).

The populations used in the denominator of the age-adjusted Alzheimer disease mortality rate are from estimates by the United Nations Population Division.

Applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as garbage codes.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The mortality rate from Alzheimer disease and other dementias is adjusted for age by direct standardization, applying estimated age-specific mortality rates, for both sexes or for a given sex, to the World Health Organization (WHO) World Standard Population.

The age-adjusted Alzheimer disease and other dementias mortality rate for 2019 was 12 per 100 000 population in country A and 7 per 100 000 population in country B; that is, in 2019 12 people died from Alzheimer disease and other dementias per 100 000 population in country A, compared to country B, where 7 people died from that cause per 100 000 population. This means that, in 2019, the population of country A had a higher risk of dying from Alzheimer disease and other dementias than in country B.

By sex

The age-adjusted mortality rate is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

The value of the age-adjusted Alzheimer disease and other dementias mortality rate will depend on the standard population used for adjustment.

The estimated value of this indicator may differ from each country’s estimates due to methodological considerations, such as: the use of a different group of ICD-10 codes for the underlying cause of death, the method for preparing population estimates and projections, or the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Estimating the Alzheimer disease and other dementias mortality rate requires a civil registry system with good coverage. Deaths must be recorded in a timely manner in this system, and certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from:
https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

- Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Sociodemographic

Socioeconomic

The percentage annual growth rate of gross domestic product (GDP) at market prices based on constant local currency for a given national economy over a specific period, usually one year. It expresses the variation between the GDP values of one period and the next as a proportion of the GDP of the previous period, usually multiplied by 100. Aggregates are expressed in U.S. dollars at constant 2010 prices to facilitate the calculation of countries' growth rates and the aggregation of country data.

GDP at buyer's prices is the sum of the gross value added of all products in the economy, plus any taxes on the products and minus any subsidies not included in the value of the products. GDP is calculated without deductions for depreciation of manufactured assets or for depletion and degradation of natural resources. Value added is the value of producers' gross output minus the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production.

Percentage

Rate

Corrected

Annual GDP growth is used to assess variations in a country's economic output over a specific period.

It contributes to evaluating changes in a country's productive capacity and eventually, alongside other indicators, its population's standard of living.

The average annual GDP growth rates are those estimated by the World Bank from the corresponding data provided by the United Nations System of National Accounts, expressed in United States dollars at constant 2010 prices.

The United Nations System of National Accounts requires that value added be valued at basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers, but excluding sales or value-added taxes). Both valuations exclude transport costs that producers invoice separately. Total GDP is measured at buyer's prices. Value added by industry is normally measured at basic production prices. GDP growth rates and their components are calculated using the least squares method and constant price data in the local currency. Constantly priced US dollar series are used to calculate regional and income group growth rates. Local currency series are converted to constant U.S. dollars using an exchange rate in the common reference year.

The growth rate per least squares is estimated by adjusting a linear regression trend line to the annual logarithmic values of the variable in the relevant period. The calculated growth rate is an average rate that represents the observations available throughout the period. The value obtained may differ from the actual growth rate between two periods

According to 2019 data, the annual percentage growth of country A's GDP was 2.0%. This means that the economic productivity of this country grew by 2.0% between 2018 and 2019.

No disaggregation

Because this indicator is based on the GDP percentage change, it is affected by its limitations, including that its value is insufficient to assess variations in the true standard of living of its inhabitants.

An increase in the percentage annual growth rate of a country's GDP between two periods may be due to a greater concentration of wealth in the higher economic strata. This may mask situations of extreme poverty or deterioration of the wellbeing and social development of its inhabitants.

The frequency with which countries' National Accounts are updated—sometimes a matter of years—is one of the methodological aspects that limit the estimates of this indicator. Another challenge is estimating the added value of the industry, since this requires detailed information on the price structure of inputs and products. This information is not always available.

World Bank. Open Data & Databank. World Development Indicators. Available from:
https://data.worldbank.org/indicator

For the most recent data, see the primary source (World Bank).

United Nations (UN). Department of Economic and Social Affairs. Sustainable Development Goals.
Indicator 8.1.1 Annual growth rate of real GDP per capita.
Available from: https://sdgs.un.org/goals

Economic Commission for Latin America and the Caribbean (ECLAC) - CEPALSTAT. Statistical Databases and Publications. Available from:
https://statistics.cepal.org/portal/cepalstat/dashboard.html?lang=en

Morbidity

Communicable diseases

The number of new confirmed cases of malaria recorded in an epidemiological year in a given country, territory, or geographical area. Expressed per 1 000 people under surveillance. The annual parasite index (API) indicates high, moderate, low, and very low-risk transmission environments.

1 000 people under surveillance

Rate

Crude

Malaria is an often-deadly parasitic disease, borne by female Anopheles mosquitoes. Despite the associated risk, especially for children, the disease is preventable and curable. Prevention is based on anti-vector measures, such as insecticide-treated nets and intra-household residual spraying, and prophylactic treatment, only in case of travel to an endemic area, because it can stop the infection in its blood stage, preventing the disease. The second pillar of malaria control is early diagnosis and treatment to reduce incidence, prevent deaths, and contribute to reducing transmission.

API highlights clinical malaria and provides less information about the potential number of asymptomatic infections. It is useful as a surveillance technique to monitor increasing or decreasing trends in malaria burden.

This indicator is used to monitor countries progressing towards targets established in the Global Technical Strategy for Malaria 2016–2030. It also contributes to monitoring national progress on the objectives of the Monitoring Framework for Universal Health in the Americas.

The indicator makes it possible to assess the temporal and geographical trends of malaria and identify at-risk populations in need of strengthened surveillance programs, disease elimination activities, and access to interventions, especially integrated and quality diagnosis and treatment. The value of the indicator is considered when allocating economic, human, and technological resources.

API is reported by each country's surveillance system. This information is reported annually to the World Health Organization in the World Malaria Report.

Formula:
(A/B) x 1 000
Numerator (A):
Confirmed cases for 1 year in a given country, territory, or geographic area.

Denominator (B):
Population under surveillance in a given country, territory, or geographic area.

In 2019, the annual parasite index of malaria in country A was 10.0 per 1,000 people; that is, during that year one new case was confirmed for every 10 people in the population under surveillance.

No disaggregation

The value of this indicator is impacted by the effectiveness of surveillance systems, which in turn may be affected by low diagnostic suspicion and underreporting of cases, the availability of laboratory tests for diagnosis, and whether private health centers report identified cases. Another factor influencing its value are areas with poorly defined at-risk populations.

API is mainly calculated from confirmed and reported symptomatic cases of parasitological malaria. As a result, API may underestimate infection incidence in highly endemic areas, and be especially inaccurate in less endemic areas.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO). Malaria surveillance, monitoring & evaluation: a reference manual. Washington, D.C., 2018. Available from: https://iris.paho.org/bitstream/handle/10665.2/50648/9789275320563_spa.pdf?ua=1

Pan American Health Organization (PAHO). Regional Program on Malaria. Available from: https://www3.paho.org/hq/index.php?option=com_content&view=article&id=1979:2010-regional-program-on-malaria&Itemid=2153&lang=en

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho/indicator-metadata-registry

World Health Organization (WHO). The Seventy-fourth World Health Assembly. Recommitting to accelerate progress towards malaria elimination. Draft Resolution A74/B/CONF./2. May 2021. Avaialbe from: https://apps.who.int/gb/ebwha/pdf_files/WHA74/A74_BCONF2-en.pdf

World Health Organization (WHO). WHO malaria terminology. Geneva, 2022. Updated in November 2021. Available from: https://www.who.int/publications/i/item/9789240038400

Sociodemographic

Demographic

Average annual rate of change in the size of the population residing in a given country, territory, or geographical area, during a specific period. Expresses the ratio between the annual increase in population size and the average population for the same period.

The annual increase in population size is defined as the sum of differences: births minus deaths and immigrants minus emigrants, in a given country, territory, or geographical area in a given year.

Average population: assuming the reference period is year z and that births are evenly distributed throughout that period, the average population will be represented by a mid-year estimate, that is, on 1 July.

Percentage

Rate

Corrected/Predicted

This indicator reflects the growth rate of a country or geographical area and is influenced by variations in birth, mortality, and migration.

It is used to analyze the temporal and geographical variations of a population's growth.

Results can be directly applied to plan and assess health and other specific public policies, such as territorial planning and resource allocation.

The annual population growth rate is generally based either on the growth rate between censuses, calculated from two censuses adjusted for census omission, or on the components of population growth, i.e. births, deaths, immigration and emigration, adjusted for underreporting if necessary, during a specific period.

The value of this indicator comes from United Nations estimates, based on data representing estimated mid-year values, obtained by linear interpolation of the corresponding United Nations five-year medium-variant population projections.

In 2018, the annual population growth rate of country A was 1.2%. This means that, during that year, this country's population increased by 1.2 people per 100 inhabitants.

No disaggregation

The international comparability of this indicator may be affected by the frequency of population censuses and demographic surveys. Population censuses are usually conducted every 10 years and survey frequency varies between different countries, with sampling error also a factor. The value of the indicator also depends on adequate coverage of the civil registry (greater than 90 percent), timely registration of deaths and births in the system, and the integrity of the registry.

Since population estimates are used to calculate the annual population growth rate, its outcome depends on the method used to develop population estimates, and projections and may differ from the results obtained at the country level.

The use of the rate in population projections for years significantly separated from the last demographic census means that recent changes in demographic dynamics may not be reflected. This tends to be higher in small populations.

United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects. Available from:
https://population.un.org/wpp/

Annual

Not applicable

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from:
https://www.who.int/data/gho/indicator-metadata-registry

United Nations, Department of Economic and Social Affairs. 2019 Demographic Yearbook, 70th Issue. New York, 2020. Available from: https://unstats.un.org/unsd/demographic-social/products/dyb/

United States Census Bureau. International Database. Glossary. Available from: https://www.census.gov/glossary/

United Nations, Department of Economic and Social Affairs, Population Divions. Glossary of Demographic Terms. Available from:
https://population.un.org/wpp/GlossaryOfDemographicTerms/

Economic Commission for Latin America and the Caribbean (ECLAC) - CEPALSTAT. Statistical Databases and Publications. Available from:
https://statistics.cepal.org/portal/cepalstat/dashboard.html?lang=en

Pan American Health Organization. Basic Health Indicators in Brazil: concepts and applications, 2nd edition. Brasilia, 2008. Available from: https://www.paho.org/bra/dmdocuments/indicadores.pdf

Health service coverage

Maternal and reproductive health

The number of women with a live birth that received four or more prenatal health checkups during pregnancy, in relation to the total number of live births, expressed as a percentage, in a given country, territory, or geographical area, in a given year.

Percentage

Proportion

Crude

Prenatal care makes it possible to prevent and identify complications in the mother and child. As such, it is closely related to the reduction of fetal, maternal, and neonatal morbidity and mortality. Prenatal check-ups also increase the chances of access to birth care by trained staff and allow interventions related to health promotion and parenting skills development, along with social and psychological support for the expectant mother.

This indicator makes it possible to identify populations that need increased coverage, availability, and access to maternal and child health services, and raises awareness of inequities in health. It can be applied during planning, management, and evaluation of health policies and maternal and child health services.

Numerator: Number of women with a live birth who have received four or more prenatal checkups during a specific period. Data includes all sectors, such as private, public and social.

Denominator: Total number women with a live birth during the same period.

The data comes from countries' routine information systems.

In 2019, prenatal care coverage in country A was 85%. This means that 85 out of every 100 women who had a live birth during that year received four or more prenatal checkups.

No disaggregation

This indicator does not allow for evaluation of the quality of the health care received, nor differentiation among professionals providing the care (doctors, nurses, midwives) or the type of care received during prenatal checkups. Availability or accessibility to this type of health service also cannot be evaluated.

The outcome of this indicator is limited by the country's ability to record in a timely manner all prenatal checkups and live births that occurred during a given period. The definition of live birth may differ between countries.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from:
https://opendata.paho.org/en/core-indicators

WHO. 2018 Global Reference List of 100 Core Health Indicators (plus health-related SDGs). Available from: https://apps.who.int/iris/bitstream/handle/10665/259951/WHO-HIS-IER-GPM-2018.1-eng.pdf?sequence=1&isAllowed=y

World Health Organization. WHO recommendations on antenatal care for a positive pregnancy experience. Geneva, 2016. Available from: https://www.who.int/publications/i/item/9789241549912

UNICEF. Antenatal care. Available from: https://data.unicef.org/topic/maternal-health/antenatal-care/

Sociodemographic

Demographic

Average births in a specific year for a certain country, territory or geographical area, usually estimated at mid-year.

Thousands

Magnitude

Corrected/Predicted

Facilitates quantification of births that occur in a given country or geographic area during a specific period. It is used as a denominator to estimate key demographic indicators, such as birth and fertility rates.

The value of this indicator comes from United Nations estimates, based on data representing estimated mid-year values, obtained by linear interpolation of the corresponding United Nations five-year medium-variant population projections.

In country A there were 2 286 300 births in 2018.

No disaggregation

The international comparability of this indicator may be affected by the frequency of population censuses and demographic surveys. Population censuses are usually conducted every 10 years and survey frequency varies between different countries, with sampling error also a factor. The value of the indicator also depends on the adequacy of civil registry coverage (greater than 90 percent), timely registration of births in the system, the integrity of the national registry, and how newborns who die during childbirth or within 24 hours of birth are registered.

The estimated value of this indicator may differ from country statistics due to factors such as methodological differences in developing population estimates and projections.

Other influencing factors are differences in how life events are defined, geographical coverage, and tabulation procedures applied in each country.

United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects. Available from:
https://population.un.org/wpp/

Annual

Not applicable

United States Census Bureau. International Programs, Glossary. Available from:
https://www.census.gov/programs-surveys/international-programs/about/glossary.html

United Nations, Department of Economic and Social Affairs, Statistics Division. Demographic and Social Statistics. Glossary of Demographic Terms. Available from:
https://population.un.org/wpp/GlossaryOfDemographicTerms/

United Nations, Department of Economic and Social Affairs. 2019 Demographic Yearbook, 70th Issue. New York, 2020. Available from: https://unstats.un.org/unsd/demographic-social/products/dyb/

Health service coverage

Maternal and reproductive health

The number of births attended at health facilities in relation to total births, in a specific country, territory, or geographic area in a given year. Expressed as a percentage.

Percentage

Proportion

Crude/Corrected

Births attended at health facilities are closely related to care by trained personnel in a health care settings, which contributes to reducing maternal and neonatal morbidity and mortality, since it makes it possible to prevent, identify, and treat complications, such as hemorrhage or sepsis, when they occur.

This indicator makes it possible to identify those populations in which health facility coverage, availability, and accessibility for childbirth care needs to be improved and maternal and child health programs need to be strengthened. It helps to highlight health inequities and to estimate the need for health facilities and their distribution for maternal and childcare.
In countries where the indicator of births attended by trained personnel is not actively reported, the proportion of births attended at health facilities is used as a proxy indicator. This is common when a high proportion of births are attended by health professionals.

Numerator: Number of births at health facilities in a given year. The data cover care in all sectors, namely the private and public sectors.

Denominator: Total number of births in the country, territory, or geographic area in the same period.

Health facilities are defined as sites that provide health care and have the resources to provide safe maternal care. They include hospitals, clinics, outpatient care centers, and specialized care centers such as birthing centers.
The data are from countries’ routine information systems or surveys.

In 2020, 93% of births in country A were attended at health facilities; that is, 9 out of 10 births were attended at a health facility.

No disaggregation

The percentage of births attended at health facilities does not make it possible to evaluate the availability of this service or access to it, nor does it assess the quality of care received or whether they have the supplies, medical equipment, trained personnel, or adequate management for attending childbirth and its complications.

This indicator may underestimate the percentage of births attended by trained personnel, particularly in the case of home births attended by trained personnel.

This indicator’s result is influenced by the country’s capacity to register in a timely manner all births and live births that occurred in a given period of time.

National health authority

Annual

United Nations (UN). Department of Economic and Social Affairs. Sustainable Development Goals.
Indicator 3.1.2: Proportion of births attended by skilled health personnel [Proporción de partos atendidos por personal sanitario especializado].
Available from: https://sdgs.un.org/goals/goal3

Pan American Health Organization. Strategic Plan of the Pan American Health Organization 2020-2025.
Indicator 2.c Proportion of births attended at health facilities
Available from: https://www.paho.org/en/documents/paho-strategic-plan-2020-2025

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

WHO. 2018 Global Reference List of 100 Core Health Indicators (plus health-related SDGs). Available from: https://apps.who.int/iris/bitstream/handle/10665/259951/WHO-HIS-IER-GPM-2018.1-eng.pdf?sequence=1&isAllowed=y

UNICEF. Delivery care. Available from: https://data.unicef.org/topic/maternal-health/delivery-care/

Health service coverage

Maternal and reproductive health

The number of births attended by trained staff in relation to the total number of births, expressed as a percentage, in a given country, territory, or geographical area, in a given year.

Percentage

Proportion

Crude

The number of births attended by trained staff is closely related to reduced maternal and neonatal morbidity and mortality, as it allows complications such as hemorrhages or sepsis to be identified and prevented, and mothers to be referred to emergency care if necessary.

This indicator makes it possible to identify populations that need improved coverage, availability, and access to skilled childbirth care to strengthen maternal and child health programs. Health inequities are exposed and specialized training needs for health professionals in maternal and child issues can be estimated.

Numerator: Number of births attended by trained staff in a given year. Data includes all sectors, such as private, public and social.

Denominator: Total number of births during the same period. Trained staff include obstetricians, doctors and nurses trained in pregnant woman care, university midwives, and midwives who have graduated with diplomas; this does not include trained or untrained traditional birth attendants.

The data comes from countries' routine information systems.

In 2020, 90% of births in country A were attended by trained staff, meaning 9 out of 10 births were attended by a doctor, nurse, or midwife.

No disaggregation

The percentage of deliveries attended by trained staff does not allow evaluation of availability or access to this service, nor the quality of care received.

The outcome of this indicator is influenced by the country's ability to record in a timely manner all births and live births that occurred during a given period.

National health authority

Annual

United Nations (UN). Department of Economic and Social Affairs.
Sustainable Development Goals (SDG)
Indicator 3.1.2: Indicator 3.1.2: Proportion of births attended by skilled health personnel.
Available from: https://sdgs.un.org/goals/goal3

Pan American Health Organization. Strategic Plan of the Pan American Health Organization 2020-2025.
Indicator 2.d Proportion of births attended by skilled health personnel
Available from: https://www.paho.org/en/documents/paho-strategic-plan-2020-2025

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from:
https://opendata.paho.org/en/core-indicators

WHO. 2018 Global Reference List of 100 Core Health Indicators (plus health-related SDGs). Available from: https://apps.who.int/iris/bitstream/handle/10665/259951/WHO-HIS-IER-GPM-2018.1-eng.pdf?sequence=1&isAllowed=y

UNICEF. Delivery care. Available from: https://data.unicef.org/topic/maternal-health/delivery-care/

Morbidity

Cancer

The ratio of new cases of breast cancer (ICD-10 code: C50) arising among women of a given country, territory, or geographical area during a specific period (usually one year), to the total number of women in the same population and year. This indicator is age-standardized to eliminate the effect of different age structures.

Per 100 000 population

Rate

Predicted

Alongside mortality and prevalence estimates, breast cancer incidence rates provide a comprehensive assessment of the impact of the disease in 185 countries or territories, including the Region of the Americas.

The data used to estimate this indicator come from cancer registries that identify new cases occurring in a well-defined population, generating statistics to evaluate and control the impact of the disease in the population.

The age-adjusted breast cancer incidence rate provides an estimate of the average risk women have of developing this type of cancer in a given country, territory, or geographic area. Its results are used to planning and allocating economic, human, and technological resources to fight breast cancer.

As the breast cancer incidence rate is age-adjusted, comparisons can be made both within and between populations over time. Inequities in health and at-risk groups can be identified.

This indicator supports public policy-making and is essential for planning and evaluating breast cancer screening, early diagnosis, treatment, and control. It helps to focus efforts such as identifying the need to strengthen and implement cancer registries in a given population.

Data for this indicator come from national or subnational population cancer registries that are routinely maintained in the Global Cancer Observatory (GCO) 2020: Cancer Incidence in Five Continents (CI5) database.

The methods used to estimate the breast cancer incidence rate in a specific country depend on available data sources. These include projections of observed incidence rates at the national level, statistical models derived from incidence rates in the country's cancer registries or neighboring country registries, and average incidence rates in neighboring countries, among other metrics.

The breast cancer incidence rate is age-standardized and results are based on rates in populations with a standard age structure.

Standardization is necessary when comparing several populations that differ in age, as age is a major factor when determining cancer risk. An age-standardized rate is a weighted average of age-specific rates based on a standard population distribution.

In 2019, the breast cancer incidence rate in country A was 38.2 per 100 000 pop. In country B it was 70.0 per 100 000 pop. In other words, the probability of developing breast cancer in country A in 2019 was 38.2 per 100 000 pop. The risk of developing this type of cancer in country B is twice as high as in country A.

No disaggregation

The data presented at the Global Cancer Observatory are the best available for each country. However, the indicator should be interpreted with caution considering current limitations in the quality and coverage of cancer data, particularly in low- and middle-income countries.

In addition, the age-adjusted breast cancer incidence rate is not a real value. Its main purpose is to allow comparisons over time between different populations or within the same population. This indicator reflects the average risk women have of developing breast cancer in a particular country. It should not be interpreted as the individual risk of developing the cancer.

The estimated value of the age-adjusted breast cancer incidence rate depends on the standard population used for its adjustment; it may therefore differ from the calculations made by each country.

The calculation method is based on new cases of breast cancer in women. It should be noted that men can also acquire a cancer of this type; however, the number of men with breast cancer is minimal compared to women, and there is no effect on the final estimated value of the indicator.

Global Cancer Observatory (GCO). Cancer Incidence in Five Continents (CI5). Available from:
https://ci5.iarc.fr/CI5plus/Default.aspx

Annual

Not applicable

International Agency for Research on Cancer (IARC), CANCER TODAY. Available from: https://gco.iarc.fr/today/home

Bray F, Colombet M, Mery L, Piñeros M, Znaor A, Zanetti R, Ferlay J, editors (2021). Cancer Incidence in Five Continents, Vol. XI. IARC Scientific Publication No. 166. Lyon: International Agency for Research on Cancer. Available from: https://publications.iarc.fr/597

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Global Reference List of 100 Core Health Indicators (plus health-related SDGs). Available from: https://apps.who.int/iris/handle/10665/259951

Mortality

Cause of death

The estimated total number of deaths from breast cancer, in the population of women of a certain age group, in a given country, territory or geographic area during a specific year, divided by total women in that population, generally estimated in the middle of the same year (1 July), after removing the effect of differences in the age distribution. Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected

Removing the effect of a different age structure by using a standard population makes it possible to analyze the breast cancer mortality rate across populations or in the same population over time.
Its result is applicable to the design, implementation, and evaluation of health policies for the prevention and control of breast cancer and the distribution of economic, human, and technological resources, among others. Its applications include, for example, evaluating over time the effect of screening strategies on reducing mortality from this type of cancer.
It helps to identify groups of women at higher risk of dying from breast cancer and to assess the presence of specific risk factors for certain population groups and the opportunity for access to timely detection, diagnosis and treatment.

The numerator of this indicator uses breast cancer deaths from the World Health Organization (WHO) Global Health Estimates (GHE) and the civil registry and national vital statistics systems of the countries of the Region of the Americas.

The underlying cause of death corresponds to code C50 of the International Classification of Diseases, Tenth Revision (ICD-10).

The populations used in the denominator of the breast cancer mortality rate are from estimates by the United Nations Population Division.

Applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as garbage codes.
The breast cancer mortality rate is adjusted for age by direct standardization, applying estimated age-specific mortality rates to the World Health Organization (WHO) World Standard Population.
For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The age-adjusted breast cancer mortality rate for 2019 is 15.1 per 100 000 population in country A and 10.5 per 100 000 population in country B; that is, in that year this malignant neoplasm was responsible for the death of 15 women per 100 000 in country A, compared to country B, where 11 women per 100 000 died from that cause. This means that, after removing the effect of the differences in the age distribution of the population between the two countries, women in country A have a higher risk of dying from breast cancer than women in country B.

No disaggregation

The age-adjusted mortality rate is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

Due to the application of advanced statistical models, estimates may differ from each country’s results. The estimated value of the age-adjusted breast cancer mortality rate will depend on the standard population used for its adjustment; therefore, it may differ from each country’s estimates. Another methodological consideration that influences its result is the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

The calculation method is based on breast cancer deaths in women.

Estimating the breast cancer mortality rate requires a civil registry system with good coverage. Deaths must be recorded in a timely manner in that system, and certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Morbidity

Cancer

The ratio of new cases of cervical cancer (ICD-10 code: C53) among women of a given country, territory, or geographical area during a specific period (usually one year), to the total number of women in the same population and year. This indicator is age-standardized to control for the effect of different age structures.

Per 100 000 population

Rate

Predicted

Alongside mortality and prevalence estimates, cervical cancer incidence rates provide a comprehensive assessment of the impact of the disease in 185 countries or territories, including the Region of the Americas.

The data used to estimate this indicator come from cancer registries that identify new cases occurring in a well-defined population, generating statistics to evaluate and control the impact of the disease in the population.

The age-adjusted cervical cancer incidence rate provides an estimate of the average risk women have of developing this type of cancer in a given country, territory, or geographic area. Results of the indicator are used to planning and allocating economic, human, and technological resources to fight cervical cancer. It can be applied, for example, to evaluate over time of the effect of implementing immunoprevention strategies against this cancer.

As the cervical cancer incidence rate is age-adjusted, comparisons can be made both within and between populations over time. It helps to identify groups of at-risk women, determine the presence of specific risk factors for particular groups, and assess timely access to diagnosis and treatment.

This indicator supports public policy-making and is essential for planning and evaluating cervical cancer screening, early diagnosis, treatment, and control. It helps to focus efforts such as identifying the need to strengthen and implement cancer registries in a given population.

Data for this indicator come from national or subnational population cancer registries that are routinely maintained in the Global Cancer Observatory (GCO) 2020: Cancer Incidence in Five Continents (CI5) database.

The methods used to estimate the cervical cancer incidence rate in a specific country depend on available data sources. These include projections of observed incidence rates at the national level, statistical models derived from incidence rates in the country's cancer registries or neighboring country registries, and average incidence rates in neighboring countries, among other metrics.

The cervical cancer incidence rate is age-standardized and results are based on rates in populations with a standard age structure.

The age-standardized rate is a summary measure of the rate that would have been observed in a population with a standard age structure. Standardization is necessary when comparing several populations that differ in age, as age is a major factor when determining cancer risk. An age-standardized rate is a weighted average of age-specific rates based on a standard population distribution.

In 2019, the cervical cancer incidence rate in country A was 44.8 per 100 000 pop. In country B, it was 88.9 per 100 000 pop. In other words, the probability of developing cervical cancer in country A in 2019 was 44.8 per 100 000 pop. The risk of developing this type of cancer in country B is twice as high as in country A.

No disaggregation

The data presented at the Global Cancer Observatory are the best available for each country. However, the indicator should be interpreted with caution considering current limitations in the quality and coverage of cancer data, particularly in low- and middle-income countries.

In addition, the age-adjusted cervical cancer incidence rate is not a real value. Its main purpose is to allow comparisons between different populations or within the same population over time therefore, its interpretation must be done with caution. This indicator reflects the average risk women have of developing cervical cancer in a particular country. It should not be interpreted as the individual risk of developing the cancer.

The estimated value of the age-adjusted cervical cancer incidence rate depends on the standard population used for its adjustment; it may therefore differ from the calculations made by each country.

Global Cancer Observatory (GCO). Cancer Incidence in Five Continents (CI5). Available from:
https://ci5.iarc.fr/CI5plus/Default.aspx

Annual

Not applicable

International Agency for Research on Cancer (IARC), CANCER TODAY. Available from: https://gco.iarc.fr/today/home

Bray F, Colombet M, Mery L, Piñeros M, Znaor A, Zanetti R, Ferlay J, editors (2021). Cancer Incidence in Five Continents, Vol. XI. IARC Scientific Publication No. 166. Lyon: International Agency for Research on Cancer. Available from: https://publications.iarc.fr/597

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core Indicators. Available from: https://opendata.paho.org/en/core-indicators/core-indicators-dashboard

Global Reference List of 100 Core Health Indicators (plus health-related SDGs). Available from: https://apps.who.int/iris/handle/10665/259951

Mortality

Cause of death

The estimated total number of deaths from cervical cancer, in the population of women in a given country or geographic area during a specific year, divided by total women in that population, generally estimated in the middle of the same year (1 July), after removing the effect of differences in the age distribution. Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected

This indicator helps to identify groups of women at higher risk of dying from cervical cancer and to assess the presence of specific risk factors for certain population groups and the opportunity for access to timely detection, diagnosis and treatment.

Its result is applicable to the design, implementation, and evaluation of health policies for the prevention, screening, diagnosis, treatment, and control of cervical cancer and the distribution of economic, human, and technological resources, among others. Its applications include, for example, evaluating over time the effect of implementing strategies for immunoprevention, screening, and early diagnosis of this type of cancer.

Removing the effect of a different age structure by using a standard population makes it possible to analyze the cervical cancer mortality rate across populations or in the same population over time.

The numerator of this indicator uses cervical cancer deaths from the World Health Organization (WHO) Global Health Estimates (GHE) and the civil registry and national vital statistics systems of the countries of the Region of the Americas.

The underlying cause of death corresponds to code C53 of the International Classification of Diseases, Tenth Revision (ICD-10). Deaths assigned to ICD code C55, cancer of the uterus, part unspecified, and distributed pro-rata to cervix uteri cancer (C53) and corpus uteri cancer (C54).

The populations used in the denominator of the cervical cancer mortality rate are from estimates by the United Nations Population Division.

Applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as garbage codes.
The cervical cancer mortality rate is adjusted for age by direct standardization, applying estimated age-specific mortality rates to the World Health Organization (WHO) World Standard Population.
For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The age-adjusted cervical cancer mortality rate for 2019 is 25 per 100 000 population in country A and 16 per 100 000 population in country B; that is, in that year cervical cancer was responsible for the death of 25 per 100 000 women in country A, compared to country B, where 16 per 100 000 women died from that cause. This means that, after removing the effect of differences in the age distribution of the population in the two countries, women in country A had a higher risk of dying from cervical cancer than women in country B.

No disaggregation

The age-adjusted mortality rate is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

The estimated value of the age-adjusted cervical cancer mortality rate will depend on the standard population used for its adjustment; therefore, it may differ from each country’s estimates. Another methodological consideration that influences its result is the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Estimating the cervical cancer mortality rate requires a civil registry system with good coverage. Deaths must be recorded in a timely manner in that system, and certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Populations for countries:
United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects. Available from: https://population.un.org/wpp/

Annual

Pan American Health Organization. Strategic Plan of the Pan American Health Organization 2020-2025.
Indicator 10. Mortality rate due to cervical cancer
Available from: https://www.paho.org/en/documents/paho-strategic-plan-2020-2025

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

Morbidity

Communicable Diseases

Number of cholera cases in a given country, territory, or geographical area, during a specific period (usually one year). Includes cases confirmed clinically, epidemiologically, or by laboratory.

Cases

Magnitude

Crude

Cholera is an acute diarrheal infection with high epidemic potential, caused by ingesting food or water contaminated with the Vibrio cholerae bacterium. Cholera transmission is closely linked to inadequate access to clean water and sanitation facilities.
The number of cases quantifies the magnitude of the disease, reflecting a population's health status and level of socioeconomic development. It raises awareness of inequities and factors enabling transmission of Vibrio cholerae and it helps identify populations in need of guaranteed access to timely and quality health care, strengthen educational interventions and hygiene measures, and improve cholera surveillance activities.

This indicator is used to monitor countries' progress with the Ending Cholera Global Roadmap to 2030. It supports multisectoral strategies to address the disease, as well as development and assessment of public policies for universal access to drinking water and sanitation, and allocation of resources to sustain these initiatives over time. It is used to detect cholera outbreaks and analyze temporal and geographical trends in a population.

The data is primarily collected from national surveillance systems that regularly report to the Pan American Health Organization.

In country A there were 12 cases of cholera in 2019.

By sex

The value of this indicator depends on the effectiveness of surveillance systems, which in turn may be affected by low diagnostic suspicion and underreporting of cases. Other factors include poor access to laboratories with appropriate diagnostic methods, and availability of data on confirmed cases from private health centers.

In order not to hinder effective control measures, cholera should be confirmed and reported in national surveillance systems separately from other diarrheal diseases.

National cholera surveillance systems

Annual

Not applicable

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho/indicator-metadata-registry

World Health Organization (WHO). Cholera prevention and control. World Health Assembly, 71 (‎WHA71.4, 2018)‎. Available from: https://www.who.int/publications/i/item/10665-279470

Global Task Force on Cholera Control (GTFCC). Ending cholera, a global roadmap to 2030. Available from: https://www.gtfcc.org/wp-content/uploads/2019/10/gtfcc-ending-cholera-a-global-roadmap-to-2030.pdf

Mortality

Cause of death

The estimated total number of deaths from circulatory diseases in the population, in a given country, territory or geographic area during a specific calendar year, divided by the total number of this population, generally estimated in the middle of the same year (1 July), after removing the effect of differences in the age distribution. Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected

This indicator helps to identify populations at higher risk of dying from circulatory diseases and to assess the presence of risk factors, such as those associated with the environment or lifestyle.

Its result is applicable to the design, implementation, and evaluation of health policies on circulatory diseases and the distribution of economic, human, and technological resources for this group of diseases, among others.

Removing the effect of a different age distribution by using a standard population makes it possible to analyze the time trend and geographic distribution of deaths from circulatory diseases, in the same population or across populations.

The numerator of this indicator uses deaths from circulatory diseases from the World Health Organization (WHO) Global Health Estimates (GHE) and the civil registry and national vital statistics systems of the countries of the Region of the Americas.

The underlying causes of death in this category correspond to codes
I00 – I99 of the International Classification of Diseases, Tenth Revision (ICD-10).

The populations used in the denominator of the circulatory diseases mortality rate are from estimates by the United Nations Population Division.

Applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as garbage codes.

The circulatory diseases mortality rate is adjusted for age by direct standardization, applying estimated age-specific mortality rates, for both sexes or for a given sex, to the World Health Organization (WHO) World Standard Population.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The age-adjusted circulatory diseases mortality rate for 2019 was 65 per 100 000 population in country A and 51 per 100 000 population in country B; that is, in that year 65 people died from circulatory diseases per 100 000 population of country A, compared to country B, where 51 people died from the same group of causes per 100 000 population. This means that, in 2019, the population of country A had a higher risk of dying from circulatory diseases than in country B.

By sex

The age-adjusted mortality rate is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

The value of the age-adjusted circulatory diseases mortality rate will depend on the standard population used for adjustment.

The estimated value of this indicator may differ from each country’s estimates due to methodological considerations such as the method used to prepare the population estimates and projections or the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Estimating the circulatory diseases mortality rate requires a civil registry system with good coverage. Deaths must be recorded in a timely manner in this system, and certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Mortality

Cause of death

The estimated total number of deaths from cirrhosis and other chronic liver diseases in the population, in a given country or geographic area during a specific calendar year, divided by the total number of this population, generally estimated in the middle of the same year (1 July), after removing the effect of differences in the age distribution of the population. Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected

The cirrhosis mortality rate reflects a population’s health status and socio-economic development, identifies those with greater risk factors for dying from cirrhosis and other chronic liver diseases, and encourages research in this area, for example, per capita alcohol consumption and the cirrhosis mortality rate in a given population.

Its result is applicable to the design, implementation, and evaluation of health policies on cirrhosis and other chronic liver diseases and the distribution of economic, human, and technological resources for the prevention, diagnosis, treatment, and control of this group of pathologies, among others. Its applications include, for example, evaluating over time the effectiveness of interventions promoting healthy lifestyles.

The age-adjusted cirrhosis mortality rate allows for the comparison across populations or in the same population over time.

The numerator of this indicator uses deaths from cirrhosis and other chronic liver diseases, from the World Health Organization (WHO) Global Health Estimates (GHE). These estimates are based on data from multiple sources such as national civil registry systems, estimates from WHO technical programs, the United Nations and inter-agency groups, and the Global Burden of Disease, among others.

The underlying causes of death correspond to codes K70, K74 of the International Classification of Diseases, Tenth Revision (ICD-10).

The populations used in the denominator of the age-adjusted cirrhosis mortality rate are from estimates by the United Nations Population Division.

Applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as garbage codes.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The cirrhosis mortality rate is adjusted for age by direct standardization, applying estimated age-specific mortality rates, for a given sex, to the World Health Organization (WHO) World Standard Population.

The age-adjusted cirrhosis mortality rate for 2019 was 21 per 100 000 population in country A and 12 per 100 000 population in country B; that is, in 2019 cirrhosis and other chronic liver diseases were responsible for the death of 21 people per 100 000 population in country A, compared to country B, where 12 people died from the same group of causes per 100 000 population. This means that, after removing the effect of differences in the age distribution on the population of both countries, in 2019 the risk of dying from cirrhosis was greater in the population of country A.

By sex

The age-adjusted cirrhosis mortality rate is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

The estimated value of the age-adjusted cirrhosis mortality rate will depend on the standard population used for its adjustment; therefore, it may differ from each country’s estimates. Other methodological considerations that influence its result are the use of a different range of ICD-10 codes and the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Estimating this indicator requires a civil registry system with good coverage. Deaths from this group of pathologies must be recorded in a timely manner in this system, and certification of the cause of death must be of good quality and should include the etiology of the cirrhosis and other chronic liver diseases; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Mortality

Cause of death

The estimated total number of deaths from colorectal cancer in the population, in a certain country, territory, or geographic area during a specific year, divided by the total number of this population, generally estimated in the middle of the same year (1 July), after removing the effect of differences in the age distribution. Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected

This indicator helps to identify populations at higher risk of dying from colorectal cancer and to evaluate the presence of potential risk factors, such as those associated with diet or lifestyle.

It is applicable to the design, implementation, and evaluation of health policies for the prevention and control of colorectal cancer and the distribution of economic, human, and technological resources for this disease, among others. Its applications include evaluating the effect of the implementation of screening strategies, such as the fecal occult blood test, for reducing mortality from this type of cancer.

Removing the effect of a different age structure by using a standard population makes it possible to analyze the colorectal cancer mortality rate across populations or in the same population over time.

The numerator of this indicator uses deaths from colorectal cancer from the World Health Organization (WHO) Global Health Estimates (GHE). These estimates are based on data from multiple sources, such as national civil registry systems, estimates from WHO technical programs, the United Nations and inter-agency groups, and the Global Burden of Disease, among others.

The underlying causes of death correspond to codes C18 – C21 of the International Classification of Diseases, Tenth Revision (ICD-10).

The populations used in the denominator of the colorectal cancer mortality rate are from estimates by the United Nations Population Division.

Applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as garbage codes.
For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The colorectal cancer mortality rate is adjusted for age by direct standardization, applying estimated age-specific mortality rates, for both sexes or for a given sex, to the World Health Organization (WHO) World Standard Population.

The age-adjusted colorectal cancer mortality rate for 2019 is 12 per 100 000 population in country A and 6 per 100 000 population in country B; that is, in country A 12 people died from colorectal cancer per 100 000 population, compared to country B, where six died per 100 000 population. This means that, after removing the effect of differences in the age structure in the two countries, the risk of dying from colorectal cancer in 2019 is higher in country A.

By sex

The age-adjusted colorectal cancer mortality rate is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

The estimated value of the age-adjusted colorectal cancer mortality rate will depend on the standard population used for adjustment.

The estimated value of this indicator may differ from each country’s estimates due to methodological considerations such as the method used to prepare the population estimates and projections, the use of a different group of ICD-10 codes, or the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Estimating the colorectal cancer mortality rate requires a civil registry system with good coverage. Deaths must be recorded in a timely manner in the system, and certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Mortality

Communicable diseases

Ratio between the estimated total number of deaths from communicable diseases and maternal, perinatal and nutritional conditions in the population, in a given country or geographic area, during a specific calendar year, divided by the total population, generally estimated in the middle of the same year (July 1). Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected

The mortality rate from communicable diseases represents the risk of dying from this group of pathologies in a certain population or geographic area. It reflects the extent of deaths from communicable diseases in the population.

Its result is applicable to the design, implementation and evaluation of health policies for the prevention, diagnosis, and control of communicable diseases and maternal, perinatal and nutritional conditions and the distribution of economic, human and technological resources for this group of pathologies, among others. These applications include planning maternal and child, nutrition and vaccination programs and designing educational interventions and environmental sanitation measures.

It helps identify populations at higher risk of dying from communicable diseases and assess the presence of risk factors, such as deficiencies in basic environmental sanitation or in coverage of immunization programs against immunopreventable diseases.

For the numerator of this indicator, deaths from communicable diseases obtained from the World Health Organization (WHO) Global Health Estimates (GHE) are used, which were developed based on data from multiple sources, such as national civil registry systems, estimates from WHO technical programs, the United Nations and interagency groups and the Global Burden of Disease, among others.

The underlying causes of death correspond to codes A00 - B99, D50 - D53, D64.9, E00 - E02, E40 - E46, E50 - E64, G00 - G04, G14, H65 - H66, J00 - J22, N70 - N73, O00 - O99, P00 - P96, U04 of the International Classification of Diseases, Tenth Revision (ICD-10).

The populations used in the denominator for the mortality rate from communicable diseases are estimates by the United Nations Population Division.

By applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as unhelpful causes (known as garbage code).

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The mortality rate from communicable diseases in country A for 2019 was 20.2 per 100 000 population, that is, during that year 20 people died per 100 000 population of country A due to some communicable disease and maternal, perinatal and nutritional conditions.

By sex

The age-adjusted mortality rate is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time, therefore, it should be interpreted with caution.

The value of the age-adjusted mortality rate from communicable diseases and maternal, perinatal and nutritional conditions will depend on the standard population used for its adjustment.

The estimated value of this indicator may differ from each country’s calculations due to methodological considerations such as the use of a different group of ICD-10 codes for the underlying cause of death, the method for preparing population forecasts and estimates, or the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Estimating the mortality rate requires a civil registry system with good coverage, that deaths be recorded in this system in a timely manner and the certification of cause of death be of good quality, otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Mortality

Cause of death

The estimated total number of deaths from communicable diseases and maternal, perinatal, and nutritional conditions in the population, in a given country, territory or geographic area, during a specific calendar year, divided by the total number of this population, generally estimated in the middle of the same year (1 July), after removing the effect of differences in the age distribution. Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected

The age-adjusted mortality rate from communicable diseases and maternal, perinatal, and nutritional conditions helps to identify populations at higher risk of dying from this group of causes and to assess the presence of risk factors, such as socio-economic factors or those associated with sanitary and environmental conditions.

Its result is applicable to the design, implementation, and evaluation of health policies for the prevention and control of communicable diseases, and maternal, perinatal, and nutritional conditions, and the distribution of economic, human, and technological resources for these diseases, among others. These applications include the planning and evaluation of maternal and child, vaccination and nutrition programs and the design and implementation of environmental sanitation measures.

Adjusting for age allows for the comparison of this indicator across populations or in the same population over time.

The numerator of this indicator uses deaths from communicable diseases and maternal, perinatal, and nutritional conditions, from the World Health Organization (WHO) Global Health Estimates (GHE). These estimates are based on data from multiple sources, such as national civil registry systems, estimates from WHO technical programs, the United Nations and inter-agency groups, and the Global Burden of Disease, among others.

The underlying causes of death correspond to codes A00 - B99, D50 - D53, D64.9, E00 - E02, E40 - E46, E50 - E64, G00 - G04, G14, H65 - H66, J00 - J22, N70 - N73, O00 - O99, P00 - P96, U04 of the International Classification of Diseases, Tenth Revision (ICD-10).

The populations used in the denominator of the age-adjusted mortality rate from communicable diseases and maternal, perinatal, and nutritional conditions are from estimates by the United Nations Population Division.

Applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as garbage codes.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://cdn.who.int/media/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods.pdf?sfvrsn=37bcfacc_5

The mortality rate from communicable diseases and maternal, perinatal, and nutritional conditions is adjusted for age by direct standardization, applying estimated age-specific mortality rates, for both sexes or for a given sex, to the World Health Organization (WHO) World Standard Population.

The age-adjusted mortality rate from communicable diseases and maternal, perinatal, and nutritional conditions for 2019 was 23 per 100 000 population in country A and 12 per 100 000 population in country B; that is, in that year these diseases and conditions caused the death of 23 people per 100 000 population of country A, compared to country B, where 12 people died from the same group of causes per 100 000 population. This means that, in 2019, the population of country A had a higher risk of dying from communicable diseases and maternal, perinatal, and nutritional conditions than in country B.

By sex

The age-adjusted mortality rate from communicable diseases and maternal, perinatal, and nutritional conditions is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

The value of the age-adjusted mortality rate from communicable diseases and maternal, perinatal, and nutritional conditions will depend on the standard population used for adjustment.

The estimated value of this indicator may differ from each country’s estimates due to methodological considerations, such as the method used to prepare the population estimates and projections or the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Estimating the mortality rate from communicable diseases and maternal, perinatal, and nutritional conditions requires a civil registry system with good coverage. Deaths must be recorded in a timely manner in this system, and certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Risk factor

Environment

The mean annual concentration of fine suspended particles of less than 2.5 microns in diameters is a common measure of air pollution. The mean is a population-weighted average for urban population in a country.

µg/m3

Average

Corrected

Air pollution consists of many pollutants, among other particulate matter. These particles are able to penetrate deeply into the respiratory tract and therefore constitute a risk for health by increasing mortality from respiratory infections and diseases, lung cancer, and selected cardiovascular diseases.
The indicator makes it possible monitor air quality trends and the result of air pollution control measures. Air quality is related to the climate of the planet and ecosystems around the world. Its result is applicable to guide policies to raise awareness about the risk of air pollution, implement measures to reduce exposure to air pollution and reduce the risks of air pollution as beneficial strategies for climate and health, because in addition to reducing the burden of disease, it helps mitigate climate change in the short and long term.

The value of this indicator comes from estimate made by the World Health Organization (WHO), the body responsible for the custody of this and two others indicator related to air pollution and health.

Concentration of PM2.5 are regularly measured from fixed-site, population-oriented monitors located within the metropolitan areas. High-quality measurements of PM concentration from all the monitors in the metropolitan area can be averaged to develop a single estimate.

Although PM2.5 is measured at many thousands of locations throughout the world, the amount of monitors in different geographical areas vary, with some areas having little or no monitoring. In order to produce global estimates at high resolution (0.1◦ grid‐cells), additional data is required. Annual urban mean concentration of PM2.5 is estimated with improved modelling using data integration from satellite remote sensing, population estimates, topography and ground measurements.

In 2019 in country A the concentration of PM2.5 was 10µg/m3. This means that, for this year, the population weighted average of the exposure of the population in the country was 10µg/m3.

By urban, rural area

Ideally, the monitoring data used to calculate the average annual PM2.5 concentrations should be collected throughout the year, for several years, to reduce bias owing to seasonal fluctuations or to a non-representative year.
Care should be taken to ensure that the monitors used are not unduly influenced by a single source of pollution (i.e. a power plant, factory or highway); rather, the monitors should reflect exposures over a wide area.
Although it is likely that particulate matter data will be available only for larger cities, residents of agglomerations of less than 100 000 inhabitants and of rural areas are also exposed to PM from local industrial activity, transportation, biomass fuels, open burning and regional haze.
Data from different countries are of limited comparability because of:
(a) Different location of measurement stations;
(b) Different measurement methods;
(c) Different temporal coverage of certain measurements; if only part of the year was covered, the measurement may significantly deviate from the annual mean due to seasonal variability;
(d) Possible inclusion of data which were not eligible for this database due to insufficient information to ensure compliance;
(e) Heterogeneous quality of measurements;
(f) Omission of data which are known to exist, but which could not yet be accessed due to language issues or limited accessibility.

World Health Organization (WHO). The Global Health Observatory (GHO). Available at:
https://www.who.int/data/gho/indicator-metadata-registry

2 to 3 years

United Nations (UN). Department of Economic and Social Affairs. Sustainable Development Goals.
Indicator 11.6.2: Annual mean levels of fine particulate matter (e.g. PM2.5 and PM10) in cities (population weighted)
Available at: https://unstats.un.org/sdgs/metadata/

Pan American Health Organization (PAHO). Monitoring Framework for Universal Health in the Americas. Washington D.C. 2021. Available from: https://iris.paho.org/handle/10665.2/53299?locale-attribute=es

World Health Organization (WHO). Air Quality data base. Available at: https://www.who.int/data/gho/data/themes/air-pollution/who-air-quality-database

Shaddick G et al (2016). Data Integration Model for Air Quality: A Hierarchical Approach to the Global Estimation of Exposures to Ambient Air Pollution. Royal Statistical Society, arXiv:1609.0014. Available at: https://arxiv.org/abs/1609.00141

World Health Organization (WHO). Road map for an enhanced global response to the adverse health effects of air pollution. World Health Assembly, 71. (‎2018)‎. Available at:
https://apps.who.int/iris/handle/10665/276321

Health service coverage

Maternal and reproductive health

Percentage of women of reproductive age (15-49 years), or their partner, currently using a modern contraceptive method among those who do not want to have (additional) children or who want to postpone the next pregnancy, in a given country, territory, or geographical area, in a given year.

Percentage

Proportion

Corrected

This indicator is used to assess overall coverage levels for family planning programs and services, making it possible to monitor countries' progress toward achieving universal access to sexual and reproductive health services. It helps reveal health inequalities and identify populations that require targeted resources to strengthen the area of sexual and reproductive health.

Availability of and access to family planning services with modern methods helps improve maternal and child health by preventing unwanted or poorly spaced pregnancies, which are at greater risk of poor obstetric outcomes.

The prevalence of modern contraceptive use comes from estimates made by the United Nations Population Division, based on data from internationally coordinated national household surveys, such as the Demographic and Health Surveys (DHS), Reproductive Health Surveys (RHS), Multiple Indicator Cluster Surveys (MICS), Gender and Generation Surveys (GGS), and other nationally sponsored surveys.

Modern contraceptive methods include female and male sterilization, intrauterine devices (IUD), implants, injectable methods, oral contraceptive pills, male and female condoms, vaginal barrier methods (including diaphragm, cervical cap, and spermicidal foam, jelly, cream, and sponge), lactation amenorrhea method, emergency contraception, and other modern methods that are not reported separately (e.g., contraceptive patch or vaginal ring).

For more details on methodology, see:
United Nations, Department of Economic and Social Affairs, Population Division (2021). World Contraceptive Use 2021. Available from:
https://www.un.org/development/desa/pd/data/world-contraceptive-use

According to 2019 data, the prevalence of use of modern contraceptive methods in country A is 67%, meaning that, in that country, of every 100 women aged 15 to 49 years who wish to delay or prevent motherhood, 67 currently use a modern contraceptive method.

By marital status: Married/ in union, unmarried

International comparability of this indicator is affected by aspects of the design and implementation of the survey from which the data are obtained. Factors to be considered include the range of contraceptives included, and specific characteristics of the base population (age, sex, marital status, etc.). The time frame used to assess contraceptive prevalence can also vary.

United Nations, Population Division. Available from: https://www.un.org/development/desa/pd/data/sdg-indicator-371-contraceptive-use

Annual

United Nations (UN). Department of Economic and Social Affairs.
Sustainable Development Goals (SDG).
Indicator 3.7.1. Proportion of women of reproductive age (aged 15–49 years) who have their need for family planning satisfied with modern methods.
Available from: https://sdgs.un.org/goals

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from:
https://opendata.paho.org/en/core-indicators

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from:
https://www.who.int/data/gho/indicator-metadata-registry

United Nations. Population Division. World Contraceptive Use. Available from:
https://www.un.org/development/desa/pd/data/world-contraceptive-use

United Nations. Sustainable Development Goals (SDG). E-Learning tool for SDG Indicator 3.7.1. Available from:
https://www.un.org/development/desa/pd/file/10712

Mortality

Cause of death

The estimated total number of deaths from corpus uteri cancer, in the population of women in a given country, territory or geographic area during a specific calendar year, divided by total women in that population, generally estimated in the middle of the same year (1 July), after removing the effect of differences in the age distribution. Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected

Removing the effect of a different age structure by using a standard population makes it possible to analyze the corpus uteri cancer mortality rate across populations or in the same population over time.

Its result is applicable to the design, implementation, and evaluation of health policies for the prevention, diagnosis, treatment, and control of corpus uteri cancer and the distribution of economic, human, and technological resources, among others. Its applications include, for example, quantifying specialized health personnel and infrastructure needed to address this type of cancer.

It helps to identify groups of women at higher risk of dying from corpus uteri cancer and to assess the presence of specific risk factors for certain population groups and the opportunity for access to timely diagnosis and treatment.

The numerator of this indicator uses corpus uteri cancer deaths from the World Health Organization (WHO) Global Health Estimates (GHE) and the civil registry and national vital statistics systems of the countries of the Region of the Americas.

The populations used in the denominator of the corpus uteri cancer mortality rate are from estimates by the United Nations Population Division.

The underlying causes of death correspond to codes C54 of the International Classification of Diseases, Tenth Revision (ICD-10). Deaths assigned to ICD code C55, cancer of the uterus, part unspecified, and distributed pro-rata to cervix uteri cancer (C53) and corpus uteri cancer (C54).

Applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as garbage codes.

The corpus uteri cancer mortality rate is adjusted for age by direct standardization, applying estimated age-specific mortality rates to the World Health Organization (WHO) World Standard Population.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The age-adjusted corpus uteri cancer mortality rate for 2019 is 15 per 100 000 population in country A and 12 per 100 000 population in country B; that is, in that year 15 women per 100 000 in country A died from uterine cancer, compared to country B, where 12 women died from that cause per 100 000. This means that, after removing the effect of differences in the age structure in the population of the two countries, in 2019 women in country A had a higher risk of dying from corpus uteri cancer than women in country B.

No disaggregation

The age-adjusted mortality rate is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

The value of the age-adjusted corpus uteri cancer mortality rate will depend on the standard population used for adjustment.

The estimated value of this indicator may differ from each country’s estimates due to methodological considerations such as the method used to prepare the population estimates and projections or the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Estimating the mortality rate from corpus uteri cancer requires a civil registry system with good coverage. Deaths must be recorded in a timely manner in this system, and certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from:
https://www.who.int/data/global-health-estimates

Populations for countries:
United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects. Available from: https://population.un.org/wpp/

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No.31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

Sociodemographic

Demographic

The ratio between the number of births in a population during a specific year and the total population for the same year.

Per 1 000 population

Rate

Corrected/Predicted

This indicator is used for planning, implementation, development, and evaluation of public policies related to maternal and childcare. It allows evaluation of the effect of implementing birth control or birth incentivization strategies. It is also used to distribute human, economic, and technological resources necessary for perinatal health programs.

The crude birth rate is an indicator of population growth. Alongside the crude mortality rate, these indicators evaluate the level of aging in a population and estimate its natural growth.

If based on a standardized reference population, temporal and geographical birth rate trends between different countries or within the same country over time can be evaluated and compared. The indicator can also be applied to make projections on health care.

The value of this indicator comes from United Nations estimates, based on data representing estimated mid-year values, obtained by linear interpolation of the corresponding United Nations five-year medium-variant population projections.

It represents how often births occur in a population.

The crude birth rate of country A for the five-year period 2015–2020 was 19.9 per 1 000 inhabitants. In Country B, it was 40.0 per 1 000 inhabitants. This means that, during this period, country A had 19.9 live births per 1 000 inhabitants, or half of the births of neighboring country B.

No disaggregation

The international comparability of this indicator may be limited by factors such as the quality of population censuses and demographic surveys used to make calculations, including misinterpretation of questions or memory bias. Estimating the birth rate requires a national civil registry with adequate coverage (greater than 90 per cent) and timely birth registration.

The estimated value of this indicator may differ from country statistics due to factors such as methodological differences in developing population estimates and projections.

Its value can be affected by variations in the sex and age structure of the population being analyzed. Because the confounding effect of age persists in this indicator, its value should not be used to make comparisons between different populations or even within the same population over time.

The crude birth rate includes births, which are only one component of population change. As such, this indicator shouldn't be confused with the growth rate, which considers all components of change (births, deaths, and migratory movements).

It should not be compared with the fertility rate, because the latter is not affected by variations in the age structure of the population and considers women in its denominator.

United Nations, Department of Economic and Social Affairs, Population Division. Available from: https://population.un.org/wpp/

Annual

Not applicable

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Avaiable from:
https://www.who.int/data/gho/indicator-metadata-registry

Economic Commission for Latin America and the Caribbean (ECLAC) - CEPALSTAT. Statistical Databases and Publications. Available from:
https://statistics.cepal.org/portal/cepalstat/dashboard.html?lang=en

United Nations, Department of Economic and Social Affairs. 2019 Demographic Yearbook, 70th Issue. New York, 2020. Available from: https://unstats.un.org/unsd/demographic-social/products/dyb/

Pan American Health Organization. Basic Health Indicators in Brazil: concepts and applications, 2nd edition. Brasilia, 2008. Available from:
https://www.paho.org/bra/dmdocuments/indicadores.pdf

Sociodemographic

Demographic

The ratio between the number of deaths in a population during a specific year and the total population for the same year.

Per 1 000 population

Rate

Corrected/Predicted

Reflects the health status and socioeconomic or environmental conditions of a population. Can be applied to design and assess health policies. Its value encourages research on the causes of death and predominant risk factors in order to implement specific preventive and control strategies. It identifies vulnerable populations and focuses interventions.

Based on a standardized reference population, it is possible to analyze temporal and geographical mortality trends and comparisons between different populations and within the same population over time.

It can be used to estimate natural population growth, or the difference between births and deaths, and is calculated by subtracting the crude mortality rate from the crude birth rate.

The value of this indicator comes from United Nations estimates, based on data representing estimated mid-year values, obtained by linear interpolation of the corresponding United Nations five-year medium-variant population projections.

The crude mortality rate of country A in 2016 was 5.9 per 1 000 inhabitants. This means that in 2016, six people died per 1 000 inhabitants in this country.

No disaggregation

The international comparability of this indicator may be affected by the frequency of population censuses and demographic surveys. Population censuses are usually conducted every 10 years and survey frequency varies between different countries, with sampling error also a factor. The value of the indicator also depends on adequate coverage of the civil registry (greater than 90 percent), timely registration of deaths in the system, and the integrity of the registry.

The estimated value of this indicator may differ from country statistics due to factors such as methodological differences in developing population estimates and projections.

The crude mortality rate is affected by the age structure of the population. Therefore, to evaluate temporal trends or to compare rates between countries or geographical areas, it must use a standardized reference population.

United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects. Available from:
https://population.un.org/wpp/

Annual

Not applicable

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from:
https://www.who.int/data/gho/indicator-metadata-registry

Economic Commission for Latin America and the Caribbean (ECLAC) - CEPALSTAT. Statistical Databases and Publications. Available from:
https://statistics.cepal.org/portal/cepalstat/dashboard.html?lang=en

United Nations, Department of Economic and Social Affairs. 2019 Demographic Yearbook, 70th Issue. New York, 2020. Available from: https://unstats.un.org/unsd/demographic-social/products/dyb/

Pan American Health Organization. Basic Health Indicators in Brazil: concepts and applications, 2nd edition. Brasilia, 2008. Available from: https://www.paho.org/bra/dmdocuments/indicadores.pdf

Haupt, A., Kane, T., Haub C. Population Reference Bureau’s Population Handbook (Sixth Edition) Washington, D.C. 2011. Available from:
https://www.prb.org/population-handbook/

Sociodemographic

Demographic

Average deaths in a specific year for a given country, territory, or geographical area, usually estimated at mid-year.

Thousands

Magnitude

Corrected/Predicted

The number of deaths shows the magnitude of deaths in a given country, territory, or geographical area. This indicator is used to estimate the crude mortality rate. By disaggregating by age or sex, the mortality rate can be estimated according to age group and sex.

The value of this indicator comes from United Nations estimates, based on data representing estimated mid-year values, obtained by linear interpolation of the corresponding United Nations five-year medium-variant population projections.

In country A there were a total of 29 400 deaths in 2018.

No disaggregation

The international comparability of this indicator may be affected by the frequency of population censuses and demographic surveys. Population censuses are usually conducted every 10 years and survey frequency varies between different countries, with sampling error also a factor. The value of the indicator also depends on adequate coverage of the civil registry (greater than 90 percent), timely registration of deaths in the system, and the integrity of the registry.

The estimated value of this indicator may differ from country statistics due to factors such as methodological differences in developing population estimates and projections.

Because the number of deaths in a given population is affected by its age structure, the value of this indicator should not be used to make comparisons between different populations or even within the same population over time.

United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects. Available from:
https://population.un.org/wpp/

Annual

Not applicable

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from:
https://www.who.int/data/gho/indicator-metadata-registry

United Nations, Department of Economic and Social Affairs. 2019 Demographic Yearbook, 70th Issue. New York, 2020. Available from: https://unstats.un.org/unsd/demographic-social/products/dyb/

Mortality

Child health

Total number of tetanus deaths registered in children under 5 in a specific country, territory, or geographic area in a given calendar year.

Deaths

Magnitude

Crude

The number of deaths from tetanus in children under 5 quantifies the impact of a preventable disease on mortality in this age group and highlights this disease as a public health problem.

This indicator supports public policy-making aimed at reducing mortality in children under 5. It makes it possible to identify areas that require the establishment or intensification of a tetanus surveillance system and to strengthen the tetanus vaccination program.

This indicator reflects the health status, living conditions, and health and socio-economic development of a population, specifically children. It helps identify health inequities and specific risk factors.

This indicator applies to the design, implementation, and evaluation of health policies for the prevention, treatment, and control of tetanus and to the distribution of economic, human, and technological resources for this disease, among others. Its main applications include promoting vaccination, improving the hygiene of medical and dental procedures, and training health care workers in the prevention and early diagnosis of this disease. It helps strengthen access to quality health care.

The number of deaths from tetanus (ICD-10 code: A35) is obtained from deaths in children under 5 in a specific country, territory, or geographic area, reported by the countries to PAHO.

In 2019, there were 27 deaths from tetanus among children under 5 in country A.

No disaggregation

This indicator refers to tetanus deaths in children under 5, which should not be confused with neonatal tetanus. Tetanus surveillance programs should be able to clearly differentiate between the neonatal and non-neonatal types.

This indicator’s value may differ from each country’s calculations due to methodological considerations, such as the application of algorithms to correct underreporting of deaths and births, and methods for redistributing ill-defined causes, among others.

Estimating the number of deaths from tetanus in children under 5 requires a civil registry system with good coverage. Births and deaths must be recorded in a timely manner in this system, and medical certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core Indicators Portal. Available from:
https://opendata.paho.org/en/core-indicators

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from:
https://www.who.int/data/gho/indicator-metadata-registry

Mortality

Child health

Total number of deaths registered due to tetanus neonatorum between 0 and 28 days of age (neonatal period) among live births in a specific country, territory, or geographic area in a given calendar year.

Tetanus is an immunopreventable disease that is acquired when spores of the bacterium Clostridium Tetani infect a wound or umbilical stump.

Deaths

Magnitude

Crude

The number of deaths due to tetanus neonatorum quantifies the impact of a preventable disease on mortality in this period and highlights this disease as a public health problem.

This indicator supports public policy-making aimed at reducing neonatal mortality. It makes it possible to identify areas that require the establishment or intensification of a neonatal tetanus surveillance system and to strengthen the tetanus vaccination program.

This indicator reflects the health status, living conditions, and health and socio-economic development of a population, specifically children. It helps identify health inequities and specific risk factors.

This indicator applies to the design, implementation, and evaluation of health policies for the prevention, treatment, and control of neonatal tetanus and to the distribution of economic, human, and technological resources for this disease, among others.

Its main applications include promoting vaccination, improving the hygiene of procedures for childbirth and newborns, and training health personnel in the prevention of this disease. It helps strengthen access to quality maternal and child health care.

The number of deaths due to tetanus neonatorum (ICD-10 code: A33) between 0 and 28 days of life (neonatal period) of live births is reported annually by the countries to PAHO.

In 2019, there were 24 deaths due to tetanus neonatorum among live births aged 0 to 28 days in country A.

No disaggregation

This indicator refers to deaths due to tetanus neonatorum, which should not be confused with non-neonatal tetanus. Tetanus surveillance programs should be able to clearly differentiate between the two types.

This indicator’s value may differ from each country’s calculations due to methodological considerations, such as the application of algorithms to correct underreporting of deaths and births, and methods for redistributing ill-defined causes, among others.

Estimating the number of deaths due to tetanus neonatorum requires a civil registry system with good coverage. Births and deaths of infant populations must be recorded in a timely manner in this system, and medical certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core Indicators Portal. Available from:
https://opendata.paho.org/en/core-indicators

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from:
https://www.who.int/data/gho/indicator-metadata-registry

Mortality

Cause of death

Proportion of deaths from communicable diseases and maternal, perinatal, and nutritional conditions in the population, in a given country or geographic area during a specific calendar year, in relation to total estimated deaths for the same place and year. Expressed as a percentage.

Percentage

Proportion

Corrected

The proportion of deaths from communicable diseases and maternal, perinatal, and nutritional conditions helps to quantify the relative importance of this group in relation to total deaths from all causes in a given population or geographic area.

Its result is applicable to the design, implementation and evaluation of health policies for the prevention and control of communicable diseases and maternal, perinatal, and nutritional conditions and the distribution of economic, human, and technological resources for this pathology, among others. Its applications include planning and evaluation of maternal and child nutrition and vaccination programs and the design and implementation of educational interventions and environmental sanitation measures.

For the percentage of deaths from communicable diseases and maternal, perinatal, and nutritional conditions, the number of deaths from this group of diseases is used as the numerator and the total number of deaths from all causes as the denominator.

Underlying causes of death correspond to codes A00 - B99, D50 - D53, D64.9, E00 - E02, E40 - E46, E50 - E64, G00 - G04, G14, H65 - H66, J00 - J22, N70 - N73, O00 - O99, P00 - P96, U04 of the International Classification of Diseases, Tenth Revision (ICD-10).

Data for this indicator are from the World Health Organization (WHO) Global Health Estimates (GHE), based on information from multiple sources, such as national civil registry systems, estimates from WHO technical programs, the United Nations and inter-agency groups, the Global Burden of Disease, and other scientific studies.

By applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death. For countries without high-quality death registration data, cause of death estimates are calculated using other data, for example, household surveys with verbal autopsy, sentinel registry systems, or special studies.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://cdn.who.int/media/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods.pdf?sfvrsn=37bcfacc_5

According to 2019 data, 5% of deaths in country A were due to communicable diseases and maternal, perinatal, and nutritional conditions; that is, for every 100 deaths from all causes in country A in 2019, five were from a communicable disease or maternal, perinatal or nutritional conditions.

By sex

The estimated value of this indicator may differ from each country’s calculations due to methodological considerations such as the use of a different group of ICD-10 codes for the underlying cause of death or the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Estimating the proportion of deaths from communicable diseases and maternal, perinatal, and nutritional conditions requires a civil registry system with good coverage. Deaths must be recorded in a timely manner in this system, and certification of cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Mortality

Cause of death

Total number of registered deaths, the selected underlying cause of which was measles, in a specific country, territory, or geographic area in a given year.

Deaths

Magnitude

Crude

The number of deaths from measles helps to quantify the importance of this disease as a public health problem for a given population or geographic area. This indicator supports public policy-making aimed at reducing mortality from this disease, mainly in children under 5 and pregnant women, which are at-risk populations.

The indicator’s result is applicable to the design, implementation, and evaluation of health policies for the prevention and control of measles and the distribution of economic, human, and technological resources for this disease. Its applications include planning and evaluation of measles vaccination programs and prioritization of health care quality.

The number of deaths from measles (ICD-10 code: B05) uses deaths in a given country, territory, or geographic area reported by the countries to PAHO.

In 2019, there were 5 deaths from measles in the population of country A.

By sex

The number of deaths from measles quantifies this disease’s impact on mortality, which should not be interpreted as the risk of dying, which is estimated by the measles mortality rate.

This indicator’s estimated value may differ from each country’s calculations due to methodological considerations, such as the application of algorithms to correct underreporting and methods for redistributing ill-defined causes, among others.

Estimating the number of deaths from measles requires a civil registry system with good coverage. Deaths must be recorded in a timely manner in this system, and certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core Indicators Portal. Available from:
https://opendata.paho.org/en/core-indicators
World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from:
https://www.who.int/data/gho/indicator-metadata-registry

World Health Organization (WHO). Measles; 2019. Available from: https://www.who.int
ews-room/fact-sheets/detail/measles

World Health Organization (WHO). Global measles and rubella strategic plan: 2012–2020. Available from: http://apps.who.int/iris/bitstream/handle/10665/94384/9789241506236_eng.pdf?sequence=1

Mortality

Noncommunicable diseases

Proportion of deaths from noncommunicable diseases in the population in a given country or geographic area during a specific calendar year, in relation to total estimated deaths for the same place and year. Expressed as a percentage.

Percentage

Proportion

Corrected

The proportion of deaths from noncommunicable diseases helps to quantify the relative importance of this group of pathologies in the mortality of a given population or geographic area.

This indicator reflects a population’s lifestyles, socioeconomic development, and health status, and is also related to population aging and rapid, poorly planned urbanization. Its analysis makes it possible to identify populations with greater risk factors for dying from noncommunicable diseases and encourage research in this area.

The proportion of deaths from noncommunicable diseases is applicable to the design, implementation, and evaluation of health policies related to this group of diseases and the distribution of economic, human, and technological resources for their prevention, diagnosis, treatment, and control, among others. Its applications include, for example, the identification of populations requiring interventions to promote healthy lifestyles or specific socioeconomic measures to reduce health inequities. It is also used to estimate the infrastructure and number of specialized health personnel required to address this group of pathologies.

Data for the percentage of deaths from noncommunicable diseases are from the World Health Organization (WHO) Global Health Estimates (GHE), based on information from multiple sources, such as national civil registry systems, estimates from WHO technical programs, the United Nations and interagency groups, the Global Burden of Disease, and other scientific studies. The number of deaths from noncommunicable diseases is used as the numerator.

The underlying causes of death for this indicator correspond to International Classification of Diseases, Tenth Revision (ICD-10) codes C00 - C97, D00 - D48, D55 - D64 (except D64.9), D65 - D89, E03 - E07, E10 - E34, E65 - E88, F01 - F99, G06 - G98 (except G14), H00 - H61, H68 - H93, I00 - I99, J30 - J98, K00 - K92, L00 - L98, M00 - M99, N00 - N64, N75 - N98, Q00 - Q99, X41 - X42, X44 - X45, R95.

By applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death. For countries without high-quality death registration data, cause of death estimates are calculated using other data, for example, household surveys with verbal autopsy, sentinel registry systems, or special studies.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000–2019. December 2020. Available from: https://cdn.who.int/media/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods.pdf?sfvrsn=37bcfacc_5

According to 2019 data, 52.4% of deaths in country A were from noncommunicable diseases; that is, for every 100 people who died in this country in 2019, noncommunicable diseases were responsible for the death of 52 of them.

By sex

The estimated value of this indicator may differ from each country’s calculations due to differences such as the method used to prepare population projections and estimates, the use of a different group of ICD-10 codes, or the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

The calculation of the proportion of deaths from noncommunicable diseases requires a civil registry system with good coverage. Deaths from this group of causes must be recorded in the system in a timely manner and certification of cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from:
https://www.who.int/data/gho/indicator-metadata-registry

Mortality

Child health

Total number of pertussis deaths registered in children under 5 in a specific country, territory, or geographic area in a given calendar year.

Deaths

Magnitude

Crude

The number of deaths from pertussis in children under 5 quantifies the importance of an immunopreventable disease on child mortality and highlights it as a public health problem for a given population or geographic area. It supports public policy-making aimed at reducing mortality in childhood.

This indicator reflects the health status, living conditions, and health and socio-economic development of a population, specifically children. It helps identify health inequities and populations with higher specific risk factors for dying from pertussis. It is directly related to coverage of the pertussis vaccination program.

This indicator is applicable to the design, implementation, and evaluation of health policies for the prevention, treatment, and control of pertussis in children and to the distribution of economic, human, and technological resources for this disease, among others. Its main applications include promoting research related to this disease, planning and evaluating pertussis vaccination programs, and prioritizing access to quality health care in children.

The number of deaths from pertussis (ICD-10 code: A37) is obtained from deaths of children under 5 in a specific country, territory, or geographic area, reported by the countries to PAHO.

In 2019, there were 24 deaths from pertussis among children under 5 in country A.

No disaggregation

The number of deaths from pertussis in children under 5 quantifies the impact of this disease on mortality in this age group. This should not be interpreted as the risk of dying, which is estimated through the pertussis mortality rate.

This indicator’s value may differ from each country’s calculations due to methodological considerations, such as the application of algorithms to correct underreporting of deaths and births, and methods for redistributing ill-defined causes, among others.

Estimating the number of deaths from pertussis in children under 5 requires a civil registry system with good coverage. Births and deaths must be recorded in a timely manner in this system, and medical certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core Indicators Portal. Available from:
https://opendata.paho.org/en/core-indicators

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from:
https://www.who.int/data/gho/indicator-metadata-registry

Mortality

Child health

Total number of deaths registered due to diphtheria in children under 5 in a given country, territory, or geographic area in a specific calendar year.

Deaths

Magnitude

Crude

The number of deaths due to diphtheria in children under 5 quantifies the importance of this disease as a public health problem for a given population or geographic area. This indicator supports public policy-making aimed at reducing mortality in this age group.

This indicator reflects the health status, living conditions, and health and socio-economic development of a population, specifically children. It helps identify health inequities and populations with higher risk factors for dying from diphtheria. It is directly related to the coverage of the diphtheria vaccination program.

This indicator is applicable to the design, implementation, and evaluation of health policies for the prevention, treatment, and control of diphtheria in children and to the distribution of economic, human, and technological resources for this disease, among other things. Its main applications include planning and evaluation of diphtheria vaccination programs, access to early antimicrobial therapy, and prioritization of the quality of health care in children.

The number of deaths due to diphtheria (ICD-10 code: A36) is from deaths of children under 5 in a given country, territory, or geographic area, reported by the countries to PAHO.

In 2019, there were 24 deaths due to diphtheria among children under 5 in country A.

No disaggregation

The number of deaths due to diphtheria in children under 5 quantifies the impact of this disease on mortality in this age group. This should not be interpreted as the risk of dying, which is estimated through the diphtheria mortality rate.

This indicator’s value may differ from each country’s calculations due to methodological considerations, such as the application of algorithms to correct underreporting of deaths and births, and methods for redistributing ill-defined causes, among others.

Estimating the number of deaths due to diphtheria in children under 5 requires a civil registry system with good coverage. Births and deaths of child populations must be recorded in a timely manner in this system, and medical certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core Indicators Portal. Available from:
https://opendata.paho.org/en/core-indicators

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from:
https://www.who.int/data/gho/indicator-metadata-registry

Health service coverage

Maternal and reproductive health

Percentage of sexually active women of reproductive age (15 to 49 years) who want no (more) children or want to postpone the next pregnancy and who are currently using a modern contraceptive method for a given country, territory or geographical area in a given year.

Percentage

Proportion

Corrected

The indicator is useful for assessing overall levels of coverage of family planning programs and services. Access to and use of an effective means of contraception helps enable women and their partners to exercise their rights to decide freely and responsibly the number and spacing of their children and to have the information and means to do so. Meeting demand for family planning with modern methods contributes to maternal and child health by preventing unintended pregnancies and closely spaced pregnancies, which are at higher risk for poor obstetrical outcomes. Satisfying family planning needs is also one of the most cost-effective investments to alleviate poverty and improve health.

Prevalence of modern contraceptive use is estimated by the United Nations Population Division, based on data from internationally coordinated national household surveys, such as the Demographic and Health Surveys (DHS), Reproductive Health Surveys (HRH), Multiple Indicator Cluster Surveys (MICS), Gender and Generation Surveys (GGS), and other nationally sponsored surveys.

The numerator in the standard definition of unmet need for family planning includes women who are fertile and sexually active, and who report that they do not want to have (more) children or who report that they want to delay the birth of their next child for at least two years or more, or who are undecided about the time of the next birth but are using a contraceptive method.

The denominator is the total number of women aged 15 to 49 who express the need for family planning, either because they are using a contraceptive method or because they have an unsatisfied need for family planning.

Modern contraceptive methods include female and male sterilization, intrauterine devices (IUD), implants, injectable methods, oral contraceptive pills, male and female condoms, vaginal barrier methods (including diaphragm, cervical cap, and spermicidal foam, jelly, cream, and sponge), lactation amenorrhea method, emergency contraception, and other modern methods that are not reported separately (e.g., contraceptive patch or vaginal ring).

For more details on methodology, see:
United Nations, Department of Economic and Social Affairs, Population Division (2021). World Contraceptive Use 2021. Available from:
https://www.un.org/development/desa/pd/data/world-contraceptive-use

According to 2019 data, met demand for family planning in country A is 52%, meaning that 52 of every 100 fertile and sexually active women who want to prevent or delay motherhood can do so by using any modern contraceptive method.

By marital status: Married/ in union, unmarried

International comparability of this indicator is affected by aspects of the design and implementation of the survey from which the data are obtained. Factors to be considered include the individual characteristics of the base population (age, sex, marital status, etc.) and the time frame used to assess met demand for family planning.

United Nations, Population Division. Available from: https://www.un.org/development/desa/pd/data/sdg-indicator-371-contraceptive-use

Annual

United Nations (UN). Department of Economic and Social Affairs.
Sustainable Development Goals (SDG).
Indicator 3.7.1. Proportion of women of reproductive age (aged 15–49 years) who have their need for family planning satisfied with modern methods. [Proporción de mujeres en edad reproductiva (de 15 a 49 años de edad) cuyas necesidades de planificación familiar se satisfacen con métodos modernos]
Available from: https://sdgs.un.org/goals

Pan American Health Organization. Strategic Plan of the Pan American Health Organization 2020-2025.
Indicator 2.a Proportion of women of reproductive age (15-49 years) who have their need for family planning satisfied with modern methods
Available from: https://www.paho.org/en/documents/paho-strategic-plan-2020-2025

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from:
https://opendata.paho.org/en/core-indicators

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from:
https://www.who.int/data/gho/indicator-metadata-registry

United Nations. Population Division. World Contraceptive Use. Available from:
https://www.un.org/development/desa/pd/data/world-contraceptive-use

United Nations. Sustainable Development Goals (SDG). E-Learning tool for SDG Indicator 3.7.1. Available from:
https://www.un.org/development/desa/pd/file/10712

Pan American Health Organization. PAHO Strategic Plan 2020-2025 “Equity at the Heart of Health” – Compendium of Outcome Indicators. Available from:
https://www.paho.org/en/documents/paho-strategic-plan-2020-2025-equity-heart-health-compendium-outcome-indicators

Morbidity

Communicable Diseases

Number of new suspected, probable, and laboratory-confirmed cases of dengue and severe dengue recorded as of 31 December of a specific year in a given country, territory, or geographical area.

Cases

Magnitude

Crude

Dengue is a viral disease transmitted mainly by the female Aedes aegypti mosquito. This species is also a vector for the chikungunya, yellow fever (urban), and Zika viruses. Aedes albopictus is a secondary vector found in the Region. Dengue has high morbidity, especially in children, and has an enormous social and economic impact. There is currently no specific treatment for this disease, so much depends on the effectiveness of preventive strategies.

This indicator makes it possible to monitor countries that are planning and implementing strategies to reduce and control Aedes aegypti populations and determine the sustainability of such measures. It helps identify populations in need of strengthened dengue surveillance programs, diagnostic capacity, and health care to address the disease.

PAHO's Strategy for Arboviral Disease Prevention and Control monitors this indicator.

It encourages research and development of new resources for dengue prevention and control. It is also used to promote intersectoral collaboration at the national and international levels and allocate human, technological, and economic resources to fight the disease.

Data are primarily collected from national surveillance systems that regularly report to the Pan American Health Organization.

In country A, there were 14 cases of dengue in 2019.

By sex

This indicator depends on the effectiveness and coverage of dengue surveillance systems, as well as diagnostic suspicion and timely case reporting.

National health authority

Annual

Not applicable

World Health Organization (WHO). Global Health Observatory (GHO). Available from: https://www.who.int/data/gho/indicator-metadata-registry

World Health Organization (WHO). Fifty-fifth World Health Assembly Dengue fever and dengue haemorrhagic fever prevention and control. Resolution WHA55.17. May 2002. Available from: https://apps.who.int/iris/bitstream/handle/10665/78534/ewha5517.pdf

World Health Organization (WHO). Dengue and severe dengue. Available from: https://www.who.int/health-topics/dengue-and-severe-dengue#tab=tab_1

Health service coverage

Human resources

Dentist density is the number of practising dentists in health facilities as of 31 December in a specific year per 10 000 population, in a given country, territory or geographic area.

The International Standard Classification of Occupations code for this category is 2261 (2008 revision).

Per 10 000 population

Ratio

Crude

Availability and access to dentists are key elements in improving the oral health of a population. This indicator makes it possible to identify inequalities in the distribution of health resources and prioritize human and economic resource allocation to specific populations. Its value is used to develop public policies increasing funding for oral health, and to train, hire, and retrain skilled workers in this area.

The indicator also contributes to monitoring country progress in implementing the Plan of Action on Human Resources for Universal Access to Health and Universal Health Coverage 2018-2023 (https://iris.paho.org/handle/10665.2/49611?locale-attribute=pt) and the Global Strategy on Human Resources for Health 2030 (https://www.who.int/publications/i/item/9789241511131).

This indicator is calculated using as numerator the number of dentists reported by the countries of the Americas to the Pan American Health Organization (PAHO). This data is collected from secondary sources, such as health workers records or databases, aggregated data from health facilities (routine administrative records, health management information systems, censuses, and surveys from the district health information system), records of councils/chambers/professional associations, active population surveys, workforce surveys, national censuses, among other verifiable sources (official scientific articles, unpublished publications, central bank accounts).

Population figures from the United Nations Population Division are used for the denominator (https://population.un.org/wpp/).

According to 2019 data, the density of dentists in country A was 1.5 per 10 000 population. This means that, practising dentists in health facilities, this country had 1.5 dentists per 10 000 population in 2019.

No disaggregation

The accuracy of this indicator depends on the coverage, recency, and quality of the data used for calculation. In general, the public health sector tends to maintain more complete data on its workers. This may lead to underestimation of the active workforce in the private health, military, non-governmental organization, and religious sectors. This professional typically works in the private sector, however, most of the time the data that is reported to the Pan American Health Organization comes from the public sector. Due to differences in data sources, there is considerable variability between countries in the coverage, regularity, quality, and integrity of the original data.

The value of this indicator may differ from figures calculated by each country due to differences such as the populations used as denominator. Another factor to consider, depending on the nature of the original data source, is that the numerator could be limited to actively working dentists or include all registered or licensed to practice professionally, even when their employment status is unknown.

National health authority

Annual

United Nations (UN). Department of Economic and Social Affairs. Sustainable Development Goals (SDG).
Indicator 3.c.1 Health worker density and distribution
Available from: https://sdgs.un.org/

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Pan American Health Organization (PAHO). Strategy on Human Resources for Universal Access to Health and Universal Health Coverage. Washington D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/34198

Pan American Health Organization (PAHO). Plan of Action on Human Resources for Universal Access to Health and Universal Health Coverage 2018-2023. Washington D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/49611?locale-attribute=pt

Pan American Health Organization (PAHO). Monitoring Framework for Universal Health in the Americas. Washington D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/53918

World Health Organization (WHO). 2018 Global Reference List of 100 Core Health Indicators (plus health-related SDGs). Geneva, 2018. Available from: https://apps.who.int/iris/bitstream/handle/10665/259951/WHO-HIS-IER-GPM-2018.1-eng.pdf

World Health Organization (WHO). National health workforce accounts: a handbook. Geneva, 2017. Available from: https://apps.who.int/iris/bitstream/handle/10665/259360/9789241513111-eng.pdf

International Labour Organization (ILO). International Standard Classification of Occupations 08 (ISCO-08). Available from: https://unstats.un.org/unsd/classifications/Family/Detail/1067

World Health Organization (WHO). Global Health Workforce statistics database. Available from: https://www.who.int/data/gho/data/themes/topics/health-workforce

Sociodemographic

Demographic

Average number of economically dependent people per 100 economically productive people in a given country, territory, or geographical area, at a specific point in time.

100 000 population

Ratio

Corrected/Predicted

This indicator reflects the inactive population segment, which must be sustained by the potentially productive portion. As a result, the indicator is related to other economic indicators and can be directly applied to develop budgetary, employment, and social security policies.

The higher the dependency rate, the greater the burden for the potentially productive population to sustain the potentially inactive population. This means that the working-age population must support a large proportion of dependents.

The indicator can also be applied to monitor the aging process of a country, territory, or geographical area.

The value of this indicator comes from United Nations estimates, based on data representing estimated mid-year values, obtained by linear interpolation of the corresponding United Nations five-year medium-variant population projections.

An economically "dependent" population is defined as the sum of the population aged 0 to 14 plus the population aged 65 and over in a given country, territory, or geographical area, at a specific point in time, usually at mid-year (July 1). The population of economically "active or productive" age is the population aged 15 to 64 in the same country, territory, or geographical area, at the same specific point in time.

Formula:
(A/B) x 100
Numerator (A):
Population under 15 years and over 65 years in a given country, territory, or geographical area in year z.

Denominator (B):
Population aged 15 to 64 in a given country, territory, or geographical area in year z.

Number of "dependent" people per 100 economically active people within a given population.

In 2015, the dependency ratio of country A was 43.8. This means in 2015, there were 43.8 dependent people for every 100 economically active people.

No disaggregation

The international quality and comparability of this indicator may be limited by factors such as inaccuracy in age reporting in censuses and demographic surveys or the methodology used to develop population estimates and projections.

In reality, these are potentially inactive and potentially active populations, because not all people aged 0 to 14 or those aged 65 and over are out of the labor market, nor are all those aged 15 to 64 working.

Because the dependency ratio is affected by factors influencing the labor market, such as including young people and older adults or excluding people of working age, this indicator should be analyzed alongside other economic parameters.

United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects. Available from:
https://population.un.org/wpp/

Annual

Not applicable

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from:
https://www.who.int/data/gho/indicator-metadata-registry

United Nations, Department of Economic and Social Affairs. 2019 Demographic Yearbook, 70th Issue. New York, 2020. Available from: https://unstats.un.org/unsd/demographic-social/products/dyb/

United States Census Bureau. International Database. Glossary. Available from:
https://www.census.gov/glossary/

United Nations, Department of Economic and Social Affairs, Population Division. Glossary of Demographic Terms. Available from:
https://population.un.org/wpp/GlossaryOfDemographicTerms/

Economic Commission for Latin America and the Caribbean (ECLAC) - CEPALSTAT. Statistical Databases and Publications. Available from:
https://statistics.cepal.org/portal/cepalstat/dashboard.html?lang=en

Pan American Health Organization. Basic Health Indicators in Brazil: concepts and applications, 2nd edition. Brasilia, 2008. Available from: https://www.paho.org/bra/dmdocuments/indicadores.pdf

Haupt, A., Kane, T., Haub C. Population Reference Bureau’s Population Handbook (Sixth Edition) Washington, D.C. 2011. Available from: https://www.prb.org/population-handbook/

Mortality

Cause of death

The estimated total number of deaths from diabetes mellitus in the population, in a given country, territory or geographic area during a specific calendar year, divided by the total number of this population, generally estimated in the middle of the same year (1 July), after removing the effect of differences in the age distribution. Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected

This indicator is applicable to the design, implementation, and evaluation of health policies related to diabetes mellitus and the distribution of economic, human, and technological resources for the prevention, diagnosis, and control of this disease, among others. Its applications include analysis of the territorial distribution of mortality from diabetes mellitus and evaluation over time of the effectiveness of interventions designed to prevent the disease.

The age-adjusted diabetes mellitus mortality rate allows for the comparison of this indicator across populations or in the same population over time.

The numerator of this indicator uses diabetes mellitus deaths from the World Health Organization (WHO) Global Health Estimates (GHE). These estimates are based on data from multiple sources, such as: national civil registry systems, estimates from WHO technical programs, the United Nations and inter-agency groups, and the Global Burden of Disease, among others.
The underlying causes of death correspond to codes E10 – E14 (except E10.2, E11.2, E12.2, E13.2, E14.2) of the International Classification of Diseases, Tenth Revision (ICD-10).

The populations used in the denominator for the age-adjusted diabetes mellitus mortality rate are from estimates by the United Nations Population Division.

Applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as garbage codes.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The diabetes mellitus mortality rate is adjusted for age by direct standardization, applying estimated age-specific mortality rates, for both sexes or for a given sex, to the World Health Organization (WHO) World Standard Population.

The age-adjusted diabetes mellitus mortality rate for 2019 was 58 per 100 000 population in country A and 15 per 100 000 population in country B; that is, in 2019 diabetes mellitus was responsible for the death of 58 people per 100 000 population of country A, compared to country B, where 15 people died from that cause per 100 000 population. This means that, in 2019, the risk of dying from diabetes mellitus was higher in the population of country A than in country B.

By sex

The age-adjusted diabetes mellitus mortality rate is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

The value of the age-adjusted diabetes mellitus mortality rate will depend on the standard population used for adjustment.

The estimated value of this indicator may differ from each country’s estimates due to methodological considerations such as the use of a different group of ICD-10 codes for the underlying cause of death, the method for preparing population estimates and projections, or the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Estimating the diabetes mellitus mortality rate requires a civil registry system with good coverage. Deaths must be recorded in a timely manner in this system, and certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Morbidity

Child health

Number of confirmed cases of diphtheria in children under 5 years of age in a given country, territory, or geographical area, in a specific calendar year. Includes laboratory or clinically confirmed or epidemiologically linked cases.

Cases

Magnitude

Crude

Diphtheria is a communicable disease with epidemic potential that can lead to death. Vaccination is one of the fundamental pillars of control. The World Health Organization (WHO) has established that all children worldwide should be vaccinated against diphtheria.

The number of confirmed cases of diphtheria in children under 5 years of age reflects the impact this disease has on children, despite being an immunopreventable disease. This indicator makes it possible to identify populations with inadequate immunization program coverage. It is applied when designing, implementing, and assessing health policies to prevent, treat, and control diphtheria in children and distribute economic, human, and technological resources to fight the disease, among other purposes. Among its main applications are planning and assessing vaccination programs against diphtheria, providing access to early antimicrobial therapy, and prioritizing quality health care in children.

It quantifies the impact of diphtheria as a public health problem in a given population or geographical area and supports decision making for public policies aimed at reducing morbidity and mortality in children under 5 years of age. Analysis of the disease's temporal and geographical trends can be performed.

This indicator reflects the health status and health and socioeconomic development of a population. It helps to identify health inequities and populations with greater risk factors for transmitting Corynebacterium diphtheriae.

The number of confirmed cases of diphtheria (ICD-10 code: A36) in children under 5 years of age is obtained from data provided by the countries of the Region of the Americas to the Pan American Health Organization (PAHO), according to information reported by national disease surveillance and control systems.

In 2019, there were 64 confirmed cases of diphtheria among children under 5 years of age residing in country A.

No disaggregation

Estimates of diphtheria cases in children under 5 years of age are affected by factors such as the effectiveness of national diphtheria surveillance systems, diagnostic suspicion, and underreporting of cases.

National health authority

Annual

United Nations (UN). Department of Economic and Social Affairs.
Sustainable Development Goals (SDG).
Indicator 3.b.1 Proportion of the target population covered by all vaccines included in their national programme.
Available from: https://sdgs.un.org/

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho/indicator-metadata-registry

World Health Organization (WHO). Diphtheria vaccine: WHO position paper. No. 31, August 2017, 92, 417–436. Available from: https://apps.who.int/iris/handle/10665/258683

Indicadores básicos para a saúde no Brasil: conceitos e aplicações, 2ª edição [Core health indicators in Brazil: concepts and applications]. Pan American Health Organization. Brasilia, 2008. Available from: https://www.paho.org/bra/dmdocuments/indicadores.pdf

Mortality

Child health

The infant mortality rate is the probability that a child born in a given country, territory, or geographic area during a specific calendar year will die before the age of 1, if subject to the age-specific mortality rates for that period.

1 000 live births

Rate

Corrected

Regarding the use of estimated (corrected) data: Since available country data vary in terms of source, definitions, and methods, a methodology was developed to produce country estimates that are representative for each country and time series and are comparable across countries.

This indicator shows the magnitude of infant deaths as a public health problem for a given population or geographic area and measures infant survival.

This value reflects the risk of infants born alive dying during their first year of life. It makes it possible to identify health inequities and populations with specific risk factors.

The infant mortality rate reflects children’s health status and social, economic, and environmental conditions. It is related to maternal and child health care access, quality, and timeliness. Its applications include strengthening professional childbirth care, breastfeeding, and vaccination programs.

This indicator is useful for designing, implementation, and evaluation of health policies and the distribution of economic, human, and technological resources aimed at improving maternal and child health. Its applications include evaluating time and geographic trends in infant mortality.

The mortality rate uses deaths of children aged 0 to 1, estimated and corrected by the Inter-agency Group for Child Mortality Estimation (IGME), for a given country or territory during a specific year as the numerator, and the total number of live births for the same population and year as the denominator.

According to the data source, the most commonly used sources for estimating the infant mortality rate are:

Civil registry: The number of deaths at age 0 and the population of that age are used to calculate the mortality rate, which is then converted into the age-specific probability of dying.

Censuses and surveys: Indirect method based on asking each woman of reproductive age how many children she has given birth to and how many are still alive. The Brass method and model life tables are then used to provide an estimate of infant mortality.

Surveys: Direct method based on birth history: a series of detailed questions about each child a woman has given birth to over her lifetime. To reduce sampling errors, estimates are generally presented as period rates, for the five or ten years leading up to the survey.

The IGME produces an infant mortality rate (IMR) trend using a standardized methodology by country groups based on the type and quality of available data. For developed countries where the civil registry has full coverage, the IMR is calculated directly from civil registry data if the data for the year to be estimated are available. For countries with an adequate trend of civil registry data, the age pattern between infant mortality and under-5 mortality from the most recent data is used as a standard for the Modified Logit Life Table developed by WHO, to convert the projected under-5 mortality rate applying a weighted regression to a projected infant mortality rate.

For countries with survey-derived data, since infant mortality rates from survey-derived birth histories are exposed to memory bias, infant mortality is obtained from projected under-5 mortality rates converted to infant mortality rates using the Coale-Demeney model life tables.

The Inter-agency Group for Child Mortality Estimation, which includes representatives from UNICEF, WHO, the World Bank, and the United Nations Population Division, is actively working to produce standardized joint estimates.

The estimated infant mortality rate of country A for 2019 was 8.3 per 1 000 live births; that is, in that year eight children died before the age of 1, per 1 000 live births in country A.

No disaggregation

The value of this indicator may differ from each country’s value due to methodological differences such as the application of methods to correct underreporting of births and deaths, statistical methods, and assumptions applied.

United Nations Inter-agency Group for Child Mortality Estimation (UN IGME). Available from: https://childmortality.org/

Annual

Not applicable

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Mortality

Maternal and reproductive health

The ratio between the number of maternal deaths and the number of live births in a given country, territory, or geographical area in a specific calendar year. Expressed per 100 000 live births.

Maternal deaths: The annual number of female deaths from any cause related to or aggravated by pregnancy or its management (excluding accidental or incidental causes) during pregnancy and childbirth or within 42 days of termination of pregnancy, irrespective of the duration and site of the pregnancy, expressed per 100,000 live births, for a specified time period.

100 000 live births

Ratio

Corrected

On the use of estimated (corrected) data: Since the available country data vary in terms of source, definition, and method, a methodology was developed to arrive at country estimates with time series that are country representative and comparable across countries.

The ratio depicts the risk of maternal death relative to the number of live births and essentially captures the risk of death in a single pregnancy or a single live birth.

In general, the maternal mortality ratio reflects the magnitude of maternal mortality, increases its visibility as a serious public health problem, and contributes to raising societal awareness about the issue. It reflects a population's state of health, as well as its socioeconomic and health development. It allows inequities in health and higher-risk populations to be identified, and highlights the need to focus economic, human, and technological resources to respond appropriately to deficiencies detected.

Its value reflects the risk that a woman has of dying from complications related to pregnancy, childbirth, or the postpartum period, and encourages research in maternal and child issues. Among its applications is the evaluation of geographical and temporal trends in maternal mortality.

This indicator is associated with the quality of women's health care, including family planning, antenatal care, attendance at childbirth, and the postpartum period. It identifies the need for specialized health personnel to prevent and treat complications that occur during pregnancy and childbirth.

Data on maternal mortality and other important variables are obtained through databases maintained by the Maternal Mortality Estimation Inter-agency Group (MMEIG), made up of the World Health Organization (WHO), the United Nations Development Programme (UNDP), the United Nations Children's Fund (UNICEF), and the World Bank Group.

MMEIG has developed a method to adjust existing data to consider data quality issues and improve the comparability of different data sources and countries. This method involves assessing underreporting and, where necessary, adjusts for insufficiency and poor classification of deaths while developing estimates through statistical models for countries without reliable data at the national level.

The estimation methods used by MMEIG consider adjustments to correct problems arising from underreporting and misclassification of maternal deaths and to ensure comparability between different data sources and countries.

The maternal mortality ratio in the Americas is 52 maternal deaths per 100 000 live births. The maternal mortality ratio of country A is 350 per 100 000 live births. This means that in country A the risk of dying due to complications occurring during pregnancy, childbirth, or the postpartum period is almost seven times greater than the regional average in the Americas.

No disaggregation

Specifically, regarding point estimates calculated with the MMEIG methodology, data may be affected by the availability of the underlying data from each country, the statistical model (including adjustment for known biases), the number of deaths in women of childbearing age, HIV, and inputs of the model, among other factors. Estimates should be considered alongside the reported margins of uncertainty within which the actual levels are known to exist.

This indicator’s value is affected by the frequency with which country data is updated, as well as transfer to the Maternal Mortality Estimation Inter-agency Group (MMEIG) for calculation.

Maternal Mortality Estimation Inter-agency Group. WHO, United Nations Children’s Fund (UNICEF), United Nations Population Fund (UNFPA), World Bank Group, and the Population Division of the Department of Economic and Social Affairs of the United Nations (UNPD).
Available from: https://mmr2020.srhr.org/homepage

Every 3-5 years

United Nations (UN). Department of Economic and Social Affairs. Sustainable Development Goals.
Indicator 3.1.1: Maternal mortality ratio
Target 3.1 of the SDG: By 2030, reduce the global maternal mortality ratio to less than 70 per 100,000 live births.
Available from: https://sdg.data.gov/

Pan American Health Organization. Strategic Plan of the Pan American Health Organization 2020-2025.
Indicator 6. Maternal mortality ratio (MMR) (deaths per 100,000 live births)
Available from: https://www.paho.org/en/documents/paho-strategic-plan-2020-2025

Estimates by WHO, UNICEF, UNFPA, World Bank Group and the UNDESA/ Population Division. Trends in maternal mortality 2000 to 2020. Geneva: World Health Organization; 2023.
Available from: https://www.who.int/publications/i/item/9789240068759

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from:
https://opendata.paho.org/en/core-indicators

Mortality

Child health

The estimated neonatal mortality rate is the probability that a child born alive will die before the age of 28 days, in a given country, territory, or geographic area during a specific calendar year. Expressed per 1 000 births.

1 000 live births

Rate

Corrected

Regarding the use of estimated (corrected) data: Since available country data vary in terms of source, definitions, and methods, a methodology was developed to produce estimates that are representative for each country and time series and are comparable across countries.

This indicator quantifies the scope of neonatal mortality as a public health problem for a given population or geographic area. It measures the risk of children born alive dying before the age of 28 days.

The estimated neonatal mortality rate reflects health status and the social, economic, and environmental conditions in which a population lives, particularly the infant population. It makes it possible to identify health inequities and populations with specific risk factors and is related to maternal and child health care access, quality, and timeliness.

This indicator is applicable to the design, implementation, and evaluation of health policies and the distribution of economic, human, and technological resources aimed at improving maternal and child health, particularly prenatal and neonatal care. Its result helps strengthen professional care for childbirth, breastfeeding, and the Expanded Program on Immunization.

It allows for analysis of the geographic and time trend of neonatal mortality in a given population.

The neonatal mortality rate is obtained from the deaths before the age of 28 days of children who were born alive, estimated and corrected by the Inter-agency Group for Child Mortality Estimation.

This indicator is estimated based on data from three sources:
Civil registry: The number of live births and the number of neonatal deaths are used to calculate age-specific rates. This system provides annual data.

Household surveys: Calculations are based on complete birth history, so women are asked the date of birth of each of their children, whether the child is still alive and, if not, the child’s age at the time of death.

To ensure consistency with under-5 mortality rates (U5MR) developed for the United Nations by the Inter-agency Group for Child Mortality Estimation (IGME) and to take into account variation in measurement errors from survey to survey, country data points for U5MR and the neonatal mortality rate (NMR) were rescaled for all years to match the IGME’s latest U5MR time series estimates. This change assumes that the proportional measurement error in NMR and U5MR is equal for each data point. The following multilevel statistical model was then applied to estimate neonatal mortality rates log (NMR / 1000) = α0 + β1 * log (U5MR / 1000) + β2* ([log (U5MR / 1000)]^2) with random effects parameters for both level and trend regression parameters, and random effects parameters influenced by the country itself.

For countries with high-quality civil registry data on neonatal deaths, defined as (i) 100% complete for adults and only civil registry data are used for infant mortality; (ii) population over 800 000; and (iii) with at least three civil registry data points for all subsequent calendar windows 1990–1994, 1995–1999, 2000–2004, 2005 onwards, the same basic equation is used, but with random effects parameters for both level and trend regression parameters and random effects parameters influenced by the country itself.

Country A’s neonatal mortality rate for 2019 was 27.3 per 1 000 live births; that is, in that year 27 children born alive died before the age of 28 days per 1 000 live births.

No disaggregation

The value of this indicator may differ from each country’s value due to methodological differences such as the application of methods to correct underreporting of births and deaths, statistical methods, and assumptions applied.

United Nations Inter-agency Group for Child Mortality Estimation (UN IGME). Available from: https://www.unicef.org/

Annual

United Nations (UN). Department of Economic and Social Affairs. Sustainable Development Goals (SDG).
Indicator 3.2.2 Neonatal mortality rate.
Available from: https://sdgs.un.org/goals

Pan American Health Organization. Strategic Plan of the Pan American Health Organization 2020-2025.
Indicator 3. Neonatal mortality rate
Available from: https://www.paho.org/en/documents/paho-strategic-plan-2020-2025

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Mortality

Child health

Under-5 mortality is the probability that a child born in a given country, territory, or geographic area, in a specific calendar year, will die before the age of 5, if subject to the age-specific mortality rates for that period.

1 000 live births

Rate

Corrected/Predicted

Regarding the use of estimated (corrected) data: Since available country data vary in terms of source, definitions, and methods, a methodology was developed to produce estimates that are representative for each country, have a time series, and are comparable across countries.

This indicator highlights under-5 deaths as a public health problem for a given population or geographic area. This value makes it possible to identify health inequities and populations with specific risk factors.

It becomes relevant because most causes of death in this age group are preventable and treatable through simple, affordable interventions such as immunization, adequate nutrition, and access to safe water and basic services.

Under-5 mortality reflects children’s health status and social, economic, and environmental conditions and is related to maternal and child health care access, quality, and timeliness.

This indicator is applicable to the design, implementation, and evaluation of health policies and the distribution of economic, human, and technological resources aimed at improving maternal and child health.

Under-5 mortality is obtained from deaths estimated by the Inter-agency Group for Child Mortality Estimation.

According to data for 2019, the under-5 mortality rate in country A was 8.3 per 1 000 live births; that is, in that year eight children died before age 5 per 1 000 live births in that country.

No disaggregation

The value of this indicator may differ from each country’s value due to methodological differences such as the application of methods to correct underreporting of births and deaths, statistical methods, and the assumptions applied.

United Nations Inter-agency Group for Child Mortality Estimation (UN IGME). Available from: https://www.unicef.org/

Annual

United Nations (UN). Department of Economic and Social Affairs. Sustainable Development Goals (SDG).
Indicator 3.2.1: Under‐5 mortality rate.
Available from: https://sdg.data.gov/

Pan American Health Organization. Strategic Plan of the Pan American Health Organization 2020-2025.
Indicator 4. Under-5 mortality rate
Available from: https://www.paho.org/en/documents/paho-strategic-plan-2020-2025

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Risk factor

Child health

Percentage of infants from 0 to 5 months of age who are exclusively breastfed, for a given year, in a given country, territory, or geographic area.

Percentage

Proportion

Corrected

Breast milk contains all the nutrients, antibodies, hormones, and antioxidants necessary for proper development of the infant; exclusive breastfeeding is the single most effective intervention to boost child survival. It protects against gastrointestinal infections, decreasing the risk of death from diarrheal syndromes. Breastfeeding also strengthens the emotional bond with the mother, benefits the psychomotor, emotional, and sensory development of the child, and stimulates the formation of tissues and cell membranes. Among the benefits for the mother are better postpartum recovery, lower fertility during exclusive breastfeeding, and lower probability of breast and ovarian cancer and osteoporosis in the future.

This indicator is part of the global Monitoring Framework for Maternal, Infant and Young Child Nutrition that assesses countries' progress towards global nutrition targets. It also enables follow-up with the Monitoring Framework for Universal Health in the Americas, to measure national progress on implementing policies aimed at strengthening health systems and achieving universal health.

This indicator is applied when developing public policies to encourage exclusive breastfeeding and establish appropriate conditions. It also contributes to research on childhood morbidity and mortality.

The value of this indicator comes from estimates made by the World Health Organization (WHO). WHO and UNICEF jointly collect data on infant and young child feeding. Among the sources of information consulted are the WHO Global Data Bank on Infant and Young Child Feeding, national health or nutrition surveys, Demographic and Health Surveys (DHS), and Multiple Indicator Cluster Surveys (MICS).

Formula:
(A/B) x 100
Numerator (A):
Number of infants 0 to 5 months of age who received only breast milk the previous day, in a given country and year.

Denominator (B):
Total number of infants from 0 to 5 months of age, for the same country and year.

In country A the percentage of infants under 6 months exclusively breastfed in 2019 was 50%, i.e., of 100 infants from 0 to 5 months of age, half were fed exclusively with breastmilk.

No disaggregation

The accuracy of this indicator depends on the coverage, recency, and quality of the data used for calculation. Surveys are the main source of data. As a result, limiting factors for this indicator include survey coverage and completeness, frequency of updates, and level of understanding of the questions. It should also be kept in mind that calculation requires live births to be timely registered in a system with adequate coverage.

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho/data/indicators/indicator-details/GHO/infants-exclusively-breastfed-for-the-first-six-months-of-life-(-)

Every 3-5 years

Pan American Health Organization. Strategic Plan of the Pan American Health Organization 2020-2025.
Indicator 14.f Percentage of infants under 6 months of age who are exclusively breastfed
Available from: https://www.paho.org/en/documents/paho-strategic-plan-2020-2025

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Pan American Health Organization (PAHO). Monitoring Framework for Universal Health in the Americas. Washington, D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/53918

World Health Organization (WHO). Indicators for the Global Monitoring Framework on Maternal, Infant and Young Child Nutrition, 2014. Available from: https://cdn.who.int/media/docs/default-source
utritionlibrary/global-targets-2025/indicators_monitoringframework_miycn_background.pdf?sfvrsn=b1934036_6

World Health Organization (WHO). Maternal, infant, and young child nutrition, December 2019. Available from: https://apps.who.int/gb/ebwha/pdf_files/EB146/B146_24-en.pdf

UNICEF Data: Monitoring the situation of children and women. Available from: https://data.unicef.org/

World Health Organization and the United Nations Children's Fund (UNICEF) Indicators for assessing infant and young child feeding practices: definitions and measurement methods. Geneva: 2021. Available from: https://www.who.int/publications/i/item/9789240018389

Mortality

Cause of death

The estimated total number of deaths from external causes in the population in a given country, territory or geographic area during a specific calendar year, divided by the total number of this population, generally estimated in the middle of the same year (1 July), after removing the effect of differences in the age distribution. Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected

This indicator is applicable to the design, implementation, and evaluation of health, transportation, and public safety policies related to deaths from external causes and the distribution of economic, human, and technological resources for their prevention, among others.

The age-adjusted external causes mortality rate allows for the comparison of this indicator across populations or in the same population over time.

The numerator of this indicator uses deaths from external causes from the World Health Organization (WHO) Global Health Estimates (GHE). These estimates are based on data from multiple sources, such as: national civil registry systems, estimates from WHO technical programs, the United Nations and inter-agency groups, and the Global Burden of Disease, among others.

The underlying causes of death correspond to codes V01 - Y89 (except X41-X42, X44 - X45) of the International Classification of Diseases, Tenth Revision (ICD-10).

The populations used in the denominator for the age-adjusted external causes mortality rate are from estimates by the United Nations Population Division.

Applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as garbage codes.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The external causes mortality rate is adjusted for age by direct standardization, applying estimated age-specific mortality rates, for both sexes or for a given sex, to the World Health Organization (WHO) World Standard Population.

The age-adjusted external causes mortality rate for 2019 was 29 per 100 000 population in country A and 14 per 100 000 population in country B; that is, in 2019, 29 people died from an external cause per 100 000 population of country A, compared to country B, where 14 people died from the same group of causes per 100 000 population. This means that, in 2019, the risk of dying from external causes was higher in the population of country A than in country B.

By sex

The age-adjusted external causes mortality rate is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

The value of the age-adjusted external causes mortality rate will depend on the standard population used for adjustment.

The estimated value of this indicator may differ from each country’s estimates due to methodological considerations, such as: the use of a different group of ICD-10 codes for the underlying cause of death, the method for preparing population estimates and projections, or the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Calculating the external causes mortality rate requires a civil registry system with good coverage. Deaths from this group of causes must be recorded in a timely manner in that system, and certification of the cause of death must be of good quality, including reporting the intentionality and type of event resulting in death; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Mortality

Cause of death

The estimated total number of deaths from falls in the population, in a given country, territory or geographic area during a specific calendar year, divided by the total number of this population, generally estimated in the middle of the same year (1 July), after removing the effect of differences in the age distribution. Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected

This indicator is applicable to the design, implementation, and evaluation of health, education, and public safety policies related to deaths from falls. Its applications include, for example, helping to promote research on falls, designing safer environments, and the impact of those environments on mortality from falls over time.

The age-adjusted falls mortality rate allows for the comparison of this indicator across populations or in the same population over time.

The numerator for this indicator uses deaths from falls from the World Health Organization (WHO) Global Health Estimates (GHE). These estimates are based on data from multiple sources, such as: national civil registry systems, estimates from WHO technical programs, the United Nations and inter-agency groups, and the Global Burden of Disease, among others.

The underlying causes of death correspond to codes W00 – W19 of the International Classification of Diseases, Tenth Revision (ICD-10).

The populations used in the denominator of the age-adjusted falls mortality rate are estimates by the United Nations Population Division.

By applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as garbage codes.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The falls mortality rate is adjusted for age by direct standardization, applying estimated age-specific mortality rates, for both sexes or for a given sex, to the World Health Organization (WHO) World Standard Population.

The age-adjusted falls mortality rate for 2019 was 30 per 100 000 population in country A and 14 per 100 000 population in country B; that is, in that year 30 people died from falls per 100 000 population of country A, compared to country B where 14 people died from this cause per 100 000 population. This means that, after removing the effect of differences in the age distribution on the population in the two countries, the risk of dying from falls in 2019 was higher in the population of country A than in country B.

By sex

The age-adjusted falls mortality rate is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

The value of the age-adjusted falls mortality rate will depend on the standard population used for adjustment.

The estimated value of this indicator may differ from each country’s estimates due to methodological considerations such as the use of a different group of ICD-10 codes for the underlying cause of death, the method for preparing population estimates and projections, or the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Calculating the falls mortality rate requires a civil registry system with good coverage. Deaths from this group of causes must be recorded in a timely manner in that system, and certification of the cause of death must be of good quality, which includes reporting how the fall leading to death occurred; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from:
https://www.who.int/data/gho/indicator-metadata-registry

Mortality

Child health

The quotient between the sum of stillbirths in a specific calendar year and the number of births (live births plus stillbirths) in the same year, for a given country, territory, or geographic area, expressed per 1 000 births.

A stillbirth corresponds to the death of the product of conception, before his expulsion or his removal from his mother's body, weighing at least 1 000 g. When the weight cannot be obtained, a full 28 weeks of gestation is used as a reference. Fetal death does not include termination of pregnancy by induction.

Per 1 000 births

Rate

Crude

The fetal mortality rate reflects the risk of a fetus dying as a result of changes during pregnancy or childbirth. It shows the magnitude of stillbirths as a public health problem for a given population or geographic area. It makes it possible to identify health inequities and populations with specific risk factors.

This indicator is related to health care during pregnancy and childbirth and to a population’s health status and socioeconomic development. Its value is used to strengthen professional childbirth care.

The fetal mortality rate is applicable to the design, implementation, and evaluation of health policies and the distribution of economic, human, and technological resources aimed at improving maternal and child health.

The fetal mortality rate uses stillbirths reported by the national health agency as the numerator and the total number of births (live births plus stillbirths) for the same population and year as the denominator. For international comparison of fetal mortality, stillbirths are limited to a weight of at least 1 000 g or 28 weeks gestation. (ICD-10)

Formula:
(A/B) x 1 000

Numerator (A):
Number of stillbirths in year z in a given country, territory or geographic area.

Denominator (B):
Total number of births (stillbirths + live births) in year z in the same country, territory or geographic area.

According to 2019 data, the fetal mortality rate in country A was 3.2 per 1 000 births; that is, in that year there were three stillbirths per 1000 births in that country.

No disaggregation

Estimating the fetal mortality rate requires a civil registry system with good coverage. Stillbirths and live births must be recorded in a timely manner in this system; otherwise, the estimates will not be sufficiently accurate.

The estimated value of the fetal mortality rate may differ from each country’s value, due to methodological differences such as the definition of stillbirth used or the application of methods to correct underreporting of births and deaths.

National health authority

Annual

Not applicable

PAHO/CLAP. Perinatal Information System (SIP). SipPlus. Available from: http://www.sipplus.org/

WHO, 2016. Making every baby count. Available from: https://www.who.int/docs/default-source/mca-documents/maternal-nb/making-every-baby-count.pdf?Status=Master&sfvrsn=6936f980_2

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

ICD-10, International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Vol 2. Available from: https://icd.who.int/browse10/Content/statichtml/ICD10Volume2_en_2016.pdf

Global Reference List of 100 Core Health Indicators (plus health-related SDGs). Available from: https://score.tools.who.int/fileadmin/uploads/score/Documents/Enable_data_use_for_policy_and_action/100_Core_Health_Indicators

Mortality

Cause of death

Total estimated number of deaths from any cause in the population in a given country or geographic area, during a specific calendar year, divided by the total population, generally estimated in the middle of the same year (July 1), after removing the effect of differences in age distribution. Expressed per 1 000 population.

Per 1 000 population

Rate

Corrected

The age-adjusted general mortality rate reflects a population’s health status and socioeconomic and environmental conditions. It makes it possible to identify those at higher risk of dying from any cause and to promote research to identify pathologies, lifestyles, external conditions, or risk factors related to this risk.

The age-adjusted general mortality rate is used to assess changes in the time and geographic trend of mortality and to make comparisons across populations.

Its result is applicable to the design, implementation, and evaluation of public policies in various areas. Its applications include the identification of populations that need to be prioritized in allocating economic, human, and technological resources to increase their life expectancy.

The numerator for this indicator is all-cause deaths from the World Health Organization (WHO) Global Health Estimates (GHE), based on data from multiple sources, such as national civil registry systems, estimates from WHO technical programs, the United Nations and interagency groups, and the Global Burden of Disease, among others.

The populations used in the denominator of the age-adjusted general mortality rate are from estimates by the United Nations Population Division.

By applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as ‘garbage codes’.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from:
https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The general mortality rate is adjusted for age through direct standardization: estimated age-specific mortality rates, for both sexes or for a given sex, are applied to the World Health Organization (WHO) World Standard Population.

The age-adjusted general mortality rate for 2019 was 5.8 per 1 000 population in country A and 4.2 per 1 000 population in country B; that is, during that year six people died from any cause per 1 000 population of country A, compared to country B, where four per 1 000 population died. This means that, after removing the effect of a different age structure in the populations of the two countries, in 2019 the risk of dying from any cause was higher in the population of country A than in country B.

By sex

The age-adjusted general mortality rate is a fictitious value. Its main purpose is to allow comparison across populations or in the same population over time. It should be interpreted with caution.

The value of the age-adjusted general mortality rate will depend on the standard population used for adjustment.

The estimated value of this indicator may differ from each country’s calculations due to methodological considerations, such as the method used to prepare the population estimates and forecasts, or the application of algorithms to correct underreporting, among others.

Calculating the age-adjusted general mortality rate requires a civil registry system with good coverage. Deaths must be recorded in the system in a timely manner; otherwise the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Sociodemographic

Socioeconomic

The Gini coefficient measures the degree of inequality in income distribution. It measures whether income distribution (or, in some cases, consumer spending) among individuals or households within an economy deviates from a perfectly equal distribution. It is calculated based on the Lorenz curve, a cumulative frequency curve that compares the empirical distribution of a variable with the uniform (equality) distribution. Uniform distribution is represented by a diagonal line. The greater the distance, or more accurately, the area between the Lorenz curve and this diagonal, the greater the inequality. The Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini coefficient measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area below the line. Therefore, a Gini coefficient of 0 represents perfect equality, while an index of 100 implies perfect inequality.

 

Index

Corrected

The Gini coefficient is one of the most common synthetic indicators to measure inequality. The adjustment method used in its estimation allows income distribution comparisons to be made between different countries or sectors of the same population.

This indicator is used to analyze temporal variations in a country's income distribution. It reflects the behavior of inequality in its population.

The estimate of this indicator is based on data on income or consumption distribution from national household surveys obtained from government statistical agencies and World Bank country departments. When original data from household surveys are available, the share of income or consumption per quintile is calculated. Otherwise, the figures are estimated from the best pooled data available. Distribution data are adjusted for household size, providing a more consistent measure of per capita income or consumption. No adjustments are made for spatial differences in the cost of living within countries, because the data needed for such calculations are generally not available.

Varies between 0 (fully equitable distribution of income) and 100 (maximum inequality in distribution). According to 2019 data, the Gini coefficient of country A was 80.7. This means that country A has a Gini coefficient close to absolute inequality (which would be represented by a hypothetical index value of 100).

No disaggregation

One limitation of the Gini coefficient is that it does not differentiate according to how inequality is distributed in the population. Because this indicator measures relative wealth and not absolute wealth, the same Gini coefficient can be obtained with two different Lorenz curves. It is also possible for the number of people in absolute poverty to decrease while the value of the indicator increases due to growing income inequality.

The accuracy of this indicator is affected by the quality of the information used to calculate it. Another aspect to consider is that because household surveys on income or consumption differ in their methodology and in the type of welfare measures collected, the data obtained are not strictly comparable between countries or even within a country in different years. Within these differences, it is the definition of income that varies most frequently in surveys. Variations in household size (number of members), income distribution, consumption needs, and age can also skew comparisons.

The Gini coefficient lacks the property of ‘additive decomposition’, by which a population's income concentration should be equal to the weighted sum of inequality in all its subgroups. Lacking this property, the Gini index is not additive between groups, that is, the total Gini of a society is not equal to the sum of the Gini indices of its subgroups.

World Bank. Open Data & Databank. World Development Indicators. Available from: https://data.worldbank.org/indicator

For the most recent data, see the primary source (World Bank).

Not applicable

Economic Commission for Latin America and the Caribbean (ECLAC) - CEPALSTAT. Stastical Databases and Publications. Availaable from:
https://statistics.cepal.org/portal/cepalstat/dashboard.html?lang=en

Sociodemographic

Socioeconomic

Gross Domestic Product (GDP) per capita based on Purchasing Power Parity (PPP)* is the gross domestic product converted into international dollars using purchasing power parity rates. An international dollar has the same purchasing power over Gross National Product as the U.S. dollar in the United States. GDP at market's prices is the sum of the gross value added of all producers residing in the economy, plus any taxes on products and minus any subsidies not included in the value of the products for a given national economy, at a given period, usually one year. Total population is a mid-year figure based on the de facto population, which counts all residents regardless of their legal status or citizenship.

PPP-adjusted International dollars

Ratio

Corrected

The Gross Domestic Product (GDP) measures a country’s total production of goods and services for final use, produced within a national territory. Its value is used to measure the wealth and economic stability of its resident population during a given period, usually one year. International comparisons between countries are possible, as GDP is based on purchasing power parity.

Purchasing Power Parity (PPP) is based on conversion rates between currencies that considers both exchange rate differences and discrepancies in price levels between countries. Therefore, when used to deflate the corresponding aggregate national accounts, they measure the real size of the economies considering the purchasing power of the currency in each country.

This indicator is used to analyze the dynamics of a country’s economy and to evaluate geographical variations in the production and social wellbeing of its inhabitants. It helps to identify gaps in the average national income production and populations with unfavorable living conditions.

Its result is used to generate social and economic policies to respond to identified needs and encourage production in certain areas of the economy.

GDP figures are estimated by the World Bank, based on figures provided by the United Nations System of National Accounts, expressed in national currency. GDP is calculated without deductions for depreciation of manufactured assets or for depletion and degradation of natural resources. Purchasing power parity conversion factors are estimated by the World Bank based on data collected by the International Comparison Program (ICP), an entity coordinated by United Nations regional economic commissions and other international organizations. Per capita figures are based on International Comparison Program (ICP) estimates.

According to 2019 data, the GDP (US$ per capita), PPP, of country A was
US$ 9 240, and of country B US$ 6 500. This means that, in this year, the total economic production of Country A adjusted for purchasing power parity was
US$ 9 240 per year for each of its inhabitants and the population of country A has more purchasing power than population B.

No disaggregation

Because this indicator does not take into account income distribution according to social stratum or geographical area, it provides insufficient information to evaluate the true standard of living of a person residing in a given country.

GDP per capita adjusted for PPP is an average value, which can be affected by wealth concentration in the highest income strata. This may mask situations of extreme poverty, and is insufficient on its own to reflect the wellbeing and social development of a country.

World Bank. Open Data & Databank. World Development Indicators. Available from:
https://data.worldbank.org/indicator

For the most recent data, see the primary source (World Bank).

Not applicable

International Comparison Program, World Bank | World Development Indicators database, World Bank | Eurostat-OECD PPP Programme.
Available from: https://www.worldbank.org/en/programs/icp

World Bank Open Data. Available from: https://data.worldbank.org/

Economic Commission for Latin America and the Caribbean (ECLAC) - CEPALSTAT. Statistical Databases and Publications. Available from:
https://statistics.cepal.org/portal/cepalstat/dashboard.html?lang=en

Sociodemographic

Socioeconomic

Gross National Income (GNI) per capita based on purchasing power parity (PPP) is GNI converted into international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GNI as the U.S. dollar in the United States.

GNI is the value of the flow of goods and services produced by residents of a country, even if these goods are produced in a foreign country. It includes products made by domestic citizens or companies and excludes foreign products or services made within the country. It is the sum of the value added by all resident producers, plus all taxes on products (minus subsidies) not included in the valuation of the product, plus net inflows of primary income (employee remuneration and property income) from abroad.

Purchasing Power Parity (PPP) is a conversion rate between currencies that considers both exchange rate differences and discrepancies in price levels between countries. Therefore, when used to deflate the corresponding national accounts aggregates, they measure the real size of economies considering the purchasing power of the currency in each country.

US$ per capita, PPP

Ratio

Corrected

The PPP-adjusted GNI value helps to assess the economic status of a country, specifically its national productive sectors. It reflects the level of national productive competitiveness in manufacturing, investment, or savings.

It helps to assess the economic growth of a country during a specific period (usually one year) and to quantify inflation or poverty, among other purposes.

Despite its limitations, it is often calculated as an indicator reflecting a population's wellbeing.

Its result is used to generate social and economic policies to respond to identified needs and incentivize productive competition in certain areas of a country.

GNI figures are estimated by the World Bank from the corresponding figures in the United Nations System of National Accounts, expressed in national currency. Purchasing power parity conversion factors are estimated by the World Bank based on data collected by the International Comparison Program (ICP), an entity coordinated by United Nations regional economic commissions and other international organizations. Per capita figures are based on World Bank population estimates and projections.

The PPP-adjusted GNI of country A during 2019 was US$ 17 740 per capita. This means that the total income produced by the country during that year, both inside and outside the national territory, was US$ 17 740 for each inhabitant, and can be compared with the value of another country.

No disaggregation

Gross National Income (GNI) should not be confused with Gross Domestic Product (GDP). The difference is that the GNI is based on the concept of nationality, which determines if a certain factor is included in its estimate. GDP is based on the country's territorial limits, calculating all the income generated within those limits, whether domestic or foreign.

This indicator does not take into account the cost of living or subsistence levels. Therefore, it provides insufficient information to assess the true wellbeing of a country and must be interpreted alongside other indicators.

Unpaid or informal work is not included the calculations. As such, it may not reflect a country's true income level.

The frequency with which countries update their data and transfer it to the World Bank for calculation affects the result of this indicator.

World Bank. Open Data & Databank. World Development Indicators. Available from:
https://data.worldbank.org/indicator

For the most recent data, see the primary source (World Bank).

Not applicable

World Bank Open Data. Available from: https://data.worldbank.org/

Economic Commission for Latin America and the Caribbean (ECLAC) - CEPALSTAT. Statistical Databases and Publications. Available from:
https://statistics.cepal.org/portal/cepalstat/dashboard.html?lang=en

Sociodemographic

Socioeconomic

Current Gross National Income (GNI) per capita is GNI converted to U.S. dollars using the World Bank's Atlas method, divided by population at mid-year. It is the sum of the value added by all resident producers, plus all taxes on products (minus subsidies) not included in the valuation of the products, plus net inflows of primary income (employee remuneration and property income) from abroad. The estimated GNI in domestic currency is usually converted into U.S. dollars using the official exchange rate to compare between economies, although an alternative exchange rate is used when the official exchange rate is estimated to diverge significantly from the exchange rate used in international transactions.

US$ per capita

Ratio

Corrected

The value of current GNI helps to assess the state of a country's economic output, whether in manufacturing, investment, or savings.

It helps to assess the economic growth of a country during a specific period (usually one year) and to quantify inflation or poverty, among other purposes.

Despite its limitations, it is often calculated as an indicator reflecting a population's wellbeing.

Its result is used to generate social and economic policies to respond to identified needs and incentivize productive competition in certain areas of a country.

GNI figures are estimated by the World Bank from the corresponding figures in the United Nations System of National Accounts, expressed in national currency. The World Bank's Atlas conversion method is used to smooth out price and exchange rate fluctuations in national income comparisons between countries. The conversion factor averages the exchange rate of a given year and the previous two years, adjusted for the difference between the country's inflation rate and that of Japan, United Kingdom, United States, and the Euro zone.

The current GNI of country A during 2019 was US$ 14 940 per capita. This means that the total income produced by the country during that year, both inside and outside the national territory, was US$ 14 940 for each of its inhabitants.

No disaggregation

Gross National Income (GNI) should not be confused with Gross Domestic Product (GDP). The difference is that GNI is based on the concept of nationality, which determines if a certain factor is included in its estimate. GDP is based on the country's territorial limits, calculating all the income generated within those limits, whether domestic or foreign.

This indicator does not take into account the cost of living or subsistence levels. Therefore, it provides insufficient information to assess the true wellbeing of a country, and it must be interpreted alongside other indicators. Unpaid or informal work is not included in its calculation. As such, it may not reflect a country's true income level.

In some countries the values of GNI and Gross Domestic Product (GDP) are quite similar, however, in others the GNI may be much higher than GDP, due to the economic aid the country receives from abroad.

The frequency with which countries update their data and transfer it to the World Bank for calculation affects the result of this indicator.

World Bank. Open Data & Databank. World Development Indicators. Available from:
https://data.worldbank.org/indicator

For the most recent data, see the primary source (World Bank).

Not applicable

World Bank Open Data. Available from: https://data.worldbank.org/

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho/indicator-metadata-registry

Pan American Health Organization/World Health Organization, Department of Evidence and Intelligence for Action in Health/Health Analysis, Metrics, and Evidence Unit. Database. Health Trends in the Americas: Core Indicators 2019. Washington, D.C., United States of America, 2019. Available from: https://iris.paho.org/handle/10665.2/51542

Pan American Health Organization. Health Information and Analysis Unit (HA). Regional Core Health Data Initiative; Core Indicators Glossary. Washington DC, June 2015. Available from:
https://www.paho.org/hq/dmdocuments/2015/glossary-eng-2014.pdf

Economic Commission for Latin America and the Caribbean - CEPALSTAT. Statistical Databases and Publications. Available from:
https://statistics.cepal.org/portal/cepalstat/dashboard.html?lang=en

Health service coverage

Human resources

Health technician density is defined as total number of practising health technicians, with formal education, in health facilities as of December 31 of a specific year, per 10 000 population in a given country, territory, or geographic area.

They carry out technical and practical tasks to support the activities of promotion, prevention, diagnosis, treatment and rehabilitation of diseases, injuries and disabilities. These occupations are classified into the following subgroups: Dental assistants and therapists, Dental prosthetists, Pharmacy assistants, Diagnostic imaging and therapeutic equipment technicians, Clinical laboratory and pathological anatomy technicians, Environmental and occupational health technicians or inspectors, Opticians, Medical Documentalists / Health Statistics Technicians, Medical Prosthetists, Traditional and Complementary Medicine Associates, Community Health Agents or Community Health Workers, Physician Assistants, Ambulance Technicians. Personnel who have been included in the categories corresponding to nursing and midwifery professionals are excluded.
The definitions of the International Standard Classification of Occupations (ISCO-08) are adapted to the context of the Region of the Americas and its countries.

Per 10 000 population

Ratio

Crude

Health technicians play a key role in providing health services. This indicator makes it possible to identify inequalities in the distribution of health resources and prioritize human and economic resource allocation to specific populations. Its value is used to develop public policies to increase funding for health, and to train, hire, and retrain skilled workers in this area.

The indicator also contributes to monitoring country progress in implementing the Plan of Action on Human Resources for Universal Access to Health and Universal Health Coverage 2018-2023 (https://iris.paho.org/handle/10665.2/49611?locale-attribute=pt) and the Global Strategy on Human Resources for Health 2030 (https://www.who.int/publications/i/item/9789241511131).

This indicator is calculated using as numerator the number of health technicians reported by the countries of the Americas to the Pan American Health Organization (PAHO). This data is collected from secondary sources, such as: health workers records or databases, aggregated data from health facilities (routine administrative records, health management information systems, censuses, and surveys from the district health information system), records of councils/chambers/professional associations, active population surveys, workforce surveys, national censuses, among other verifiable sources (official scientific articles, unpublished publications, central bank accounts).

Population figures from the United Nations Population Division are used for the denominator (https://population.un.org/wpp/).

According to 2019 data, the density of health technicians in country A was 10.5 per 10 000 population. This means that, in all health facilities, this country A had 10.5 health technicians per 10 000 population in 2019.

No disaggregation

The accuracy of this indicator depends on the coverage, recency, and quality of the data used for calculation. In general, the public health sector tends to maintain more complete data on its workers. This may lead to underestimation of the active workforce in the private health, military, non-governmental organization, and religious sectors. Due to differences in data sources, there is considerable variability between countries in the coverage, regularity, quality, and integrity of the original data.

The value of this indicator may differ from figures calculated by each country due to differences such as the populations used as denominator. Another factor to consider, depending on the nature of the original data source, is that the numerator could be limited to actively working health technicians, or include all registered or licensed, even if their employment status is unknown.

National health authority

Annual

United Nations (UN). Department of Economic and Social Affairs. Sustainable Development Goals (SDG).
Indicator 3.c.1 Health worker density and distribution
Available from: https://sdgs.un.org/

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators
Pan American Health Organization (PAHO). Strategy on Human Resources for Universal Access to Health and Universal Health Coverage. Washington D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/34198

Pan American Health Organization (PAHO). Plan of Action on Human Resources for Universal Access to Health and Universal Health Coverage 2018-2023. Washington D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/49611?locale-attribute=pt

Pan American Health Organization (PAHO). Monitoring Framework for Universal Health in the Americas. Washington D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/53918

World Health Organization (WHO). 2018 Global Reference List of 100 Core Health Indicators (plus health-related SDGs). Geneva, 2018. Available from: https://apps.who.int/iris/bitstream/handle/10665/259951/WHO-HIS-IER-GPM-2018.1-eng.pdf

World Health Organization (WHO). National health workforce accounts: a handbook. Geneva, 2017. Available from: https://apps.who.int/iris/bitstream/handle/10665/259360/9789241513111-eng.pdf

International Labour Organization (ILO). International Standard Classification of Occupations 08 (ISCO-08). Available from: https://unstats.un.org/unsd/classifications/Family/Detail/1067

World Health Organization (WHO). Global Health Workforce statistics database. Available from: https://www.who.int/data/gho/data/themes/topics/health-workforce

Mortality

Cause of death

The estimated total number of deaths from HIV/AIDS (human immunodeficiency virus/acquired immunodeficiency syndrome) in the population, in a given country, territory or geographic area during a specific calendar year, divided by the total number of this population, generally estimated in the middle of the same year, after removing the effect of differences in the age distribution. Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected/Predicted

This indicator reflects the magnitude of HIV mortality as a public health problem, helps identify populations at higher risk of dying from the disease, and helps design and evaluate specific public health interventions.

Its result is applicable to the design, implementation, and evaluation of public policies related to HIV. Its result contributes, for example, to evaluating access to and timeliness of diagnosis, coverage of antiretroviral therapies and evaluating the effectiveness of health policies aimed at HIV prevention and control.

The age-adjusted HIV mortality rate allows for the comparison of this indicator across populations or in the same population over time.

The numerator of this indicator uses deaths from the human immunodeficiency virus/ acquired immunodeficiency syndrome (HIV/AIDS), from the World Health Organization (WHO) Global Health Estimates (GHE). Empirical data from different sources on HIV/AIDS surveillance are consolidated to estimate the level and trend of HIV infection and mortality in adults and children. These sources include national civil registry systems, estimates from WHO technical programs, the United Nations, and inter-agency groups.
The underlying causes of death correspond to codes B20 – B24 of the International Classification of Diseases, Tenth Revision (ICD-10).
The populations used in the denominator of the age-adjusted HIV/AIDS mortality rate are from estimates by the United Nations Population Division.

Applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as garbage codes.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The HIV/AIDS mortality rate is adjusted for age by direct standardization, applying estimated age-specific mortality rates, for both sexes or for a given sex, to the World Health Organization (WHO) World Standard Population.

The age-adjusted HIV/AIDS mortality rate for 2019 was 22 per 100 000 population in country A and 12 per 100 000 population in country B; that is, in that year 22 people died from HIV/AIDS per 100 000 population of country A, compared to country B, where 12 people died from this cause per 100 000 population. This result indicates that, after removing effect of difference in the age distribution in the two countries, in 2019 the risk of dying from HIV/AIDS was higher in the population of country A than in country B.

By sex

The age-adjusted HIV/AIDS mortality rate is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

The estimated value of the age-adjusted HIV/AIDS mortality rate will depend on the standard population used for its adjustment; therefore, it may differ from each country’s estimates. Another methodological consideration that influences the estimate is the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Estimating this rate requires a civil registry system with good coverage. HIV/AIDS deaths must be recorded in a timely manner in that system, and certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

World Health Organization (WHO). Global HIV Programme. HIV data and statistics. Available from: https://www.who.int/teams/global-hiv-hepatitis-and-stis-programmes/hiv/strategic-information/hiv-data-and-statistics

World Health Organization (WHO). Global progress report on HIV, viral hepatitis, and sexually transmitted infections, 2021. Accountability for the global health sector strategies 2016–2021: actions for impact. Geneva, 2021. Available from: https://www.who.int/publications/i/item/9789240027077

Mortality

Cause of death

The estimated total number of deaths from homicides and intentionally inflicted injuries in the population in a given country, territory or geographic area during a specific calendar year, divided by the total number of its population, generally estimated in the middle of the same year (average population), after removing the effect of differences in the age distribution. Expressed per 100 000 population.

Per 100 000 population

Rate

Predicted

This indicator reflects the magnitude of homicide mortality as a public health problem and helps to identify populations with higher levels of violence and to design and evaluate specific public health interventions.

Its result is applicable to the design, implementation, and evaluation of public safety policies. Its result contributes, for example, to assessing the levels of violence and public safety in a country or geographic area, along with encouraging research on the causes that give rise to violence.

The age-adjusted homicide mortality rate allows for the comparison of this indicator across populations or in the same population over time.

The numerator for this indicator (also called “interpersonal violence”), uses homicides deaths from the World Health Organization (WHO) Global Health Estimates (GHE). These estimates are based on multiple sources, for example, data from police and civil registry sources provided by countries, data from the United Nations Office on Drugs and Crime (UNODC) global studies on homicides, data from the WHO mortality database, and the Global Burden of Disease, among others.

The underlying causes of death correspond to codes X85 – Y09, Y87.1 of the International Classification of Diseases, Tenth Revision (ICD-10).

The estimation process uses observed data on homicide rates, along with regression models for countries without sufficient data availability or quality, to calculate comparable estimates of homicide rates and numbers across countries.

The populations used in the denominator of the age-adjusted homicide mortality rate are from estimates by the United Nations Population Division.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The homicide mortality rate is adjusted for age by direct standardization, applying estimated age-specific mortality rates, for both sexes or for a given sex, to the World Health Organization (WHO) World Standard Population.

The age-adjusted homicide mortality rate for 2019 was 5.9 per 100 000 population in country A and 3.2 per 100 000 population in country B; that is, in country A in 2019 there were six homicides deaths per 100 000 population, compared to country B, where three people died from this cause per 100 000 population. This result indicates that, after removing the effect of differences in the age distribution in the two countries, in 2019 the risk of dying by homicide was higher in the population of country A than in country B.

By sex

The age-adjusted mortality rate from homicides is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

The estimated value of the age-adjusted homicide mortality rate will depend on the standard population used for its adjustment; therefore, it may differ from each country’s estimates. Another methodological consideration that influences this result is the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Estimating the homicide mortality rate requires a civil registry system with good coverage. Homicide deaths must be recorded in a timely manner in that system, and certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

United Nations (UN). Department of Economic and Social Affairs. Sustainable Development Goals (SDG).
Indicator 16.1.1 Number of victims of intentional homicide per 100,000 population, by sex and age
Available from: https://sdgs.un.org/goals

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

United Nations Office on Drugs and Crime (UNODC). Available from: https://www.unodc.org/unodc/en/index.html

Health system

Health service

Number of hospital beds available per thousand population in a given country, territory, or geographical area in a given year.

Number of hospital beds refers to all hospital beds in public, social and private settings, which are maintained and staffed on a regular basis and are immediately available for the care of admitted patients. They are the sum of the following four categories: (i) Acute care beds; (ii) Rehabilitation beds; (iii) Long-term care beds; and (iv) Other hospital beds. Included: Beds in all general hospitals, mental health hospitals, and other specialized hospitals; Occupied and unoccupied beds. Excluded: Operating room tables, recovery cots, emergency stretchers, beds for same-day care, cribs for healthy infants; Beds in rooms closed for any reason; Temporary beds; Beds in residential long-term care facilities.

Hospital beds per 1 000 population

Ratio

Crude

The hospital bed ratio provides a measure of the resources available to provide services to inpatients in hospitals in terms of the number of beds maintained, staffed, and immediately available for use. It helps monitor health systems, identify areas that require greater investment, and prioritize the allocation of economic, human, and technological resources. It reflects both demand- and supply-side factors and provides a rough approximation of the scope of physical, financial, and other barriers to health care in a population.

The numerator for the ratio of hospital beds is obtained from the number of hospital beds reported by the ministries of health to the Pan American Health Organization (PAHO). For the denominator, population statistics from the United Nations Population Division.

The ratio of hospital beds in country A in 2019 was 2.0 per 1 000 population. This means that, including the public, social and private health sectors, there were 2.0 hospital beds available for use per thousand population in country A that year.

No disaggregation

Although hospital beds are used to indicate the availability of inpatient services, there is no global standard for hospital bed density relative to the total population.

Due to methodological differences such as the population used as a denominator, the value of this indicator may differ from the results obtained by the country. It should also be considered that, depending on the source used and the means of monitoring, the data may not be exactly comparable between countries.

National health authority

Annual

Not applicable

Organization for Economic Co-operation and Development (OECD). OECD Data. Hospital beds (indicator). Available from:
https://data.oecd.org/healtheqt/hospital-beds.htm

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from:
https://opendata.paho.org/en/core-indicators

Health service coverage

Health service

Number of hospital intensive care unit (ICU) beds available per 100 000 population in a specific country, territory, or geographic area in a given year.

The number of ICU beds refers to all hospital beds in the public, and private sectors.

The ICU is an organized system for delivering highly complex care to critically ill patients that provides intensive, specialized medical and nursing care, enhanced monitoring capacity, and multiple advanced life-sustaining treatments during a period of acute organ system failure. It includes pediatric, neonatal, and adult ICU beds.

Hospital beds per 100 000 population

Ratio

Crude

The hospital ICU beds ratio provides a measurement of the resources available to provide services to hospitalized patients who require critical care in terms of the number of beds that are maintained, that have specialized health personnel, and that are immediately available for use. This indicator contributes to monitoring health systems, identifying areas that require greater investment, and prioritizing the allocation of economic, human, and technological resources. It reflects both demand-side and supply-side factors and provides a rough approximation of the extent of physical, financial, and other barriers, as well as the health care management capacity in a population.

The hospital ICU beds ratio uses the number of beds reported by Ministries of Health to the Pan American Health Organization (PAHO) as the numerator. Population figures from the UN Population Division are used for the denominator.

The hospital ICU beds ratio in country A in 2019 was 6 per 100 000 population; that is, including the public and private health sectors, that year there were 6 hospital beds available for use per 100 000 population of country A.

No disaggregation

Although hospital ICU beds are used to indicate the availability of services for hospitalized critical care patients, there is no global standard for bed density relative to the total population.

Due to methodological differences such as the population used in the denominator, this indicator’s value may differ from each country’s results. Moreover, depending on the definition, source and monitoring methods used, the data may not be exactly comparable across countries.

National health authority

Annual

Not applicable

Organization for Economic Co-operation and Development (OECD). Health at a Glance 2021: OECD Indicators. Hospital beds and occupancy; 2021. Available from:
https://www.oecd-ilibrary.org/social-issues-migration-health/health-at-a-glance-2021_ae3016b9-en
Pan American Health Organization (PAHO)/World Health Organization (WHO). Core Indicators Portal. Available from:
https://opendata.paho.org/en/core-indicators

Morbidity

Communicable diseases

Number of confirmed cases of human rabies in a particular country, territory, or geographical area during a specific period. This includes cases confirmed clinically, epidemiologically, or by laboratory investigation.

Cases

Magnitude

Crude

The goal of monitoring rabies numbers is to eliminate dog-transmitted human rabies on the continent. In addition, the indicator helps monitor rabies transmitted by wild animals and herbivores that are still widespread in the Americas.

Rabies is an acute zoonotic disease caused by a Rhabdoviridae virus, leading to progressive and almost certain fatal inflammation of the brain and spinal cord. It is transmitted through the saliva of infected domestic or wild mammals; the most frequent vector for human rabies is the domestic dog. Despite being lethal once clinical signs appear, rabies is totally preventable. Vaccinating dog is the primary and most cost-effective measure to prevent human rabies. Prophylactic treatment exists for humans who are exposed.

The number of cases of human rabies indicates the magnitude of the disease in the population, reflecting its health and socioeconomic development and the effectiveness of human and animal rabies control strategies. The indicator is used to identify at-risk populations in order to focus preventive strategies, especially dog vaccination and control of other mammal vectors (e.g., bats), in addition to strengthening intersectoral collaboration to fight the disease and improving surveillance systems for human and animal rabies. This indicator is also used when allocating economic, human, and technological resources.

The number of laboratory-confirmed cases of human rabies comes from data officially reported by the Ministries of Health of affected countries to the PAHO/WHO Pan American Center for Foot-and-Mouth Disease and Veterinary Public Health (PANAFTOSA/VPH). The data are mostly obtained from national surveillance systems and technical programs on human and animal rabies and collected by PANAFTOSA/VPH from official information sources, such as the Regional Information System for The Epidemiological Surveillance of Rabies (SIRVERA). Cases ruled out after laboratory investigation are not included.

In 2019, there were three confirmed cases of human rabies in country A.

By sex, transmission by domestic dog, transmission by wild animals

The value of this indicator is impacted by the effectiveness and coverage of human rabies surveillance and control systems.

National health authority

Annual

Not applicable

Pan American Health Organization/World Health Organization (PAHO/WHO). Pan American Center for Foot-and-Mouth Disease and Veterinary Public Health (PANAFTOSA/VPH). Available from: https://www.paho.org/en/panaftosa

Pan American Health Organization (PAHO). Rabies. Available from: https://www.paho.org/en/topics/rabies

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Health system

Data quality

Number of deaths whose underlying cause was assigned an ill-defined code, expressed as a percentage of total deaths in a given country, territory, or geographical area, during a specific year.

Percentage

Proportion

Crude

The percentage of ill-defined causes of death is used to assess the quality of mortality information. Quantifying the value of this indicator is essential to understand the quality and correct interpretation of causes of death and determine their effect on other mortality indicators.

Ill-defined causes of death refer to conditions that should not be considered as underlying cause (specifically signs, symptoms, or laboratory findings) and do not match the definition of underlying cause (an illness or injury that set off the chain of events directly leading to death, or the accident or violent act that produced the fatal injury). From a public health perspective, it is important to know the underlying cause in order to support prevention programs and design and implement effective policies and strategies.

Among the reasons for selecting this cause as an underlying cause on the death certificate are: insufficient case information from the certifying physician; lack of training among personnel on how to correctly certify the death; and certification authorization given to non-medical personnel that often lack training and information on underlying cause certification. Another reason is failure to train and update mortality coders.

Ill-defined causes impede targeted health interventions. For example, hypovolemic shock (an ill-defined cause) may result from gastrointestinal bleeding, a stab wound (intentional or unintentional), or postpartum obstetric bleeding. Preventive actions differ in each of the three causes, which highlights the importance of correctly specifying the underlying cause of death.

Generally speaking, causes of death statistics are essential when allocating resources to health services and planning and evaluating health policies. As a result, having correct and reliable underlying cause of death information is a public health priority.

Ill-defined underlying causes of death are: R00-R94, R96-R99 of Chapter XVIII of the ICD-10 "Symptoms, signs, and abnormal clinical and laboratory findings, not classified elsewhere".

The percentage of ill-defined causes of death is calculated by the Pan American Health Organization (PAHO) from data reported by the responsible national institution.
Formula:
(A/B) x 100

Numerator (A):
Number of deaths will ill-defined causes in year z in a given country, territory, or geographic area.

Denominator (B):
Deaths from all causes in year z in a given country, territory, or geographic area.

According to 2019 data, the percentage of ill-defined causes of death in country A was 4%, i.e., 4 out of every 100 deaths in country A that year were coded with ill-defined causes of death, and therefore are not useful in public health analyses because the true underlying cause of death is unknown.

No disaggregation

The accuracy of this indicator is impacted by the coverage of civil registration systems, timely registration of deaths, and recorded information on causes of death. For example, when there is incomplete coverage in registration systems, the proportion of deaths assigned to ill-defined causes will generally increase as coverage increases, even with no real drop in the quality of medical certification.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

University of Melbourne. Avoiding ill-defined and unusable underlying causes: The underlying condition responsible for the failure should also be reported. Available from: https://crvsgateway.info/Avoiding-ill-defined-and-unusable-underlying-causes~343

Health system

Child health

The percentage of children under 2 years of age who have received three doses of the Pneumococcal Conjugate vaccine (PCV3) in a specific year, in a given country, territory, or geographical area.

Percentage

Proportion

Crude

Pneumococcus is one of the main causes of pneumonia and meningitis in children, causing death in a high number of cases. Immunization is one of the most cost-effective public health interventions and is essential to reducing infant mortality. PCV coverage is a measure of the performance of the health system in administering childhood vaccination. Its value identifies gaps in immunization program coverage and promotes the allocation of economic, human, and technological resources to guarantee proper program functioning.

Annually, countries officially report coverage figures through the PAHO/WHO/UNICEF Joint Notification Form. The data comes from their administrative information systems. Using these figures, PAHO calculates regional coverage according to the weighted average of the United Nations population.
In some countries, the third dose is applied in children under 1 year. In others, children receive the vaccine at 1 year of age. As a result, the denominator selected is 2-year-old children.

In 2019, immunization coverage in children under 2 years of age with the third dose of pneumococcal vaccine in country A was 79%, i.e., for every 100 children of that age, 79 received three doses of pneumococcal vaccine in 2019.

No disaggregation

The value of this indicator depends on the performance of technical programs and their ability to capture data. Ideally, countries would also have a well-functioning national immunization registry. The methodology used to determine immunization coverage may differ from country to country.

National health authority

Annual

United Nations (UN). Department of Economic and Social Affairs. Sustainable Development Goals (SDG).
Indicator 3.b.1 Proportion of the target population covered by all vaccines included in their national program.
Available from: https://sdgs.un.org/

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Pan American Health Organization (PAHO). Pneumococcus: Available from: https://www.paho.org/en/topics/pneumococcus

Pan American Health Organization (PAHO). Immunization. Available from: https://www.paho.org/en/topics/immunization

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho/indicator-metadata-registry

Health system

Child health

The percentage of 1-year-old children who have received the first dose of measles vaccine (usually in combination with rubella and mumps) in a specific year, in a given country, territory, or geographic area.

Percentage

Proportion

Crude

Immunization is one of the most cost-effective public health interventions and is essential to reducing infant mortality. Measles vaccination coverage measures the performance of the health system in administering childhood vaccination. Its value identifies gaps in immunization program coverage and promotes the allocation of economic, human, and technological resources to guarantee proper program functioning. It helps measles elimination efforts to become more targeted.

Annually, countries officially report coverage figures through the PAHO/WHO/UNICEF Joint Notification Form. The data comes from their administrative information systems. Using these figures, PAHO calculates regional coverage according to the weighted average of the United Nations population.

In 2019, immunization coverage in 1-year-old children with the first dose of measles vaccine was 91% in country A; i.e., for every 100 children of that age, 91 received at least one dose of the measles vaccine in 2019.

No disaggregation

The value of this indicator depends on the performance of technical programs and their ability to capture data. Ideally, countries would also have a well-functioning national immunization registry. The methodology used to determine immunization coverage may differ from country to country.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators
Pan American Health Organization (PAHO). Immunization. Available from: https://www.paho.org/en/topics/immunization

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho/indicator-metadata-registry

Health system

Child health

The percentage of children under 1 year of age who have received a dose of the Bacille Calmette-Guérin (BCG) tuberculosis vaccine in a specific year, in a given country, territory, or geographical area.

Percentage

Proportion

Crude

Immunization is essential to reducing under-5 mortality. The Bacillus Calmette-Guérin (BCG) vaccine has been available for 80 years and is one of today's most widely used vaccines. Although it does not prevent primary infection or reactivation of latent lung infection, the BCG vaccine has a documented protective effect against meningitis and disseminated tuberculosis in children.

Estimates are used to monitor immunization service coverage and to guide efforts to eradicate and eliminate diseases, in this case, tuberculosis. This indicator measures the performance of the health system and the population's access to vaccination programs.

Annually, countries officially report coverage figures through the PAHO/WHO/UNICEF Joint Notification Form. The data comes from their administrative information systems. Using these figures, PAHO calculates regional coverage according to the weighted average of the United Nations population.

In 2019, BCG immunization coverage in children under 1 year of age in country A was 80%; i.e., 4 out of 5 children received the single dose of BCG vaccine in 2019.

No disaggregation

The value of this indicator depends on the performance of technical programs and their ability to capture data. Ideally, countries would also have a well-functioning national immunization registry. The methodology used to determine immunization coverage may differ from country to country.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators
Pan American Health Organization (PAHO). Immunization. Available from:
https://www.paho.org/en/topics/immunization

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho/indicator-metadata-registry

Health system

Child health

The percentage of children who, by the end of their first year of life, have received three doses of the diphtheria, tetanus, and pertussis vaccine (DTP) in a given country, territory, or geographic area, in a specific year.

Percentage

Proportion

Crude

Immunization is one of the most cost-effective public health interventions and is essential to reducing infant mortality. This indicator measures the performance of the health system in administering childhood vaccination. Its value identifies gaps in immunization program coverage and promotes the allocation of economic, human, and technological resources to guarantee proper program functioning.

The indicator is part of the Monitoring Framework for Universal Health in the Americas, which monitors country progress in providing access and universal health coverage.

Annually, countries officially report coverage figures through the PAHO/WHO/UNICEF Joint Notification Form. The data comes from their administrative information systems. Using these figures, PAHO calculates regional coverage according to the weighted average of the United Nations population.

In 2019, immunization coverage in children under 1 year of age with the third dose of DTP in country A was 85%; i.e., for every 100 children of that age, 85 had received all three doses of the DTP vaccine in 2019.

No disaggregation

The value of this indicator depends on the performance of technical programs and their ability to capture data. Ideally, countries would also have a well-functioning national immunization registry. The methodology used to determine immunization coverage may differ from country to country.

National health authority

Annual

United Nations (UN). Department of Economic and Social Affairs. Sustainable Development Goals (SDG).
Indicator 3.b.1 Proportion of the target population covered by all vaccines included in their national program.
Available from: https://sdgs.un.org/

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Pan American Health Organization (PAHO). Monitoring Framework for Universal Health in the Americas. Washington, D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/53918

Pan American Health Organization (PAHO). Immunization data and statistics. Available from: https://www.paho.org/en/topics/immunization/immunization-data-and-statistics

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho/indicator-metadata-registry

Health system

Child health

The percentage of children under 1 year of age who have received three doses of the polio vaccine in a specific year, in a given country, territory, or geographical area.

Percentage

Proportion

Crude

Polio is a highly contagious viral disease that causes permanent paralysis, and can lead to death. The child population is the most susceptible. Immunization is the most effective way to prevent this disease and to reduce disability and infant mortality. Polio vaccine coverage is a measure of the performance of the health system in administering childhood vaccination. The indicator's value identifies gaps in immunization program coverage and promotes the allocation of economic, human, and technological resources to guarantee proper program functioning. It enables efforts to monitor the eradication of the disease in the Region of the Americas.

Annually, countries officially report coverage figures through the PAHO/WHO/UNICEF Joint Notification Form. The data comes from their administrative information systems. Using these figures, PAHO calculates regional coverage according to the weighted average of the United Nations population.

In 2019, immunization coverage in children under 1 year of age with the third dose of polio vaccine was 86% in country A, i.e., for every 100 children of that age, 86 received three doses of polio vaccine in 2019.

No disaggregation

The value of this indicator depends on the performance of technical programs and their ability to capture data. Ideally, countries would also have a well-functioning national immunization registry. The methodology used to determine immunization coverage may differ from country to country.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Pan American Health Organization (PAHO). Immunization. Available from: https://www.paho.org/en/topics/immunization

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho/indicator-metadata-registry

Health system

Child health

The percentage of children under 1 year of age who completed their rotavirus vaccination schedule in a specific year, in a given country, territory, or geographical area.

Percentage

Proportion

Crude

Rotavirus is highly contagious and is the most common cause of severe diarrheal disease in young children worldwide, for whom it may be deadly. Rotavirus vaccine has been shown to be safe and highly effective in preventing serious illness and hospitalization. Rotavirus vaccine coverage is a measure of the performance of the health system in administering childhood vaccination. Its value identifies gaps in immunization program coverage and promotes the allocation of economic, human, and technological resources to guarantee proper program functioning.

Annually, countries officially report coverage figures through the PAHO/WHO/UNICEF Joint Notification Form. The data comes from their administrative information systems. Using these figures, PAHO calculates regional coverage according to the weighted average of the United Nations population.

This indicator is the percentage of children under 1 year of age who received the last dose of rotavirus vaccine. This may be a second or third dose depending on the vaccine used.

In 2019, rotavirus immunization coverage in children under 1 year of age was 69% in country A; i.e., for every 100 children of that age, 69 completed their rotavirus vaccination schedule in 2019.

No disaggregation

The value of this indicator depends on the performance of technical programs and their ability to capture data. Ideally, countries would also have a well-functioning national immunization registry. The methodology used to determine immunization coverage may differ from country to country.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Pan American Health Organization (PAHO). Immunization. Available from: https://www.paho.org/en/topics/immunization

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho/indicator-metadata-registry

Morbidity

Communicable diseases

The number of new cases of congenital syphilis (live births and stillbirths) reported in the last 12 months in a given country, territory, or geographical area, compared to the total number of live births in the same population and year.

1 000 live births

Rate

Crude

Congenital syphilis occurs when a pregnant woman with syphilis transmits the infection to the fetus. Untreated syphilis is a major public health problem. It is the second most frequent cause of infectious fetal death worldwide and is associated with an increased risk of neonatal death, congenital disease (congenital syphilis), premature birth, low birth weight, and HIV transmission and acquisition in mother and baby. Despite the severity, it is preventable by early diagnosis and immediate treatment of the mother during prenatal care.

The incidence of congenital syphilis is considered when evaluating strategies designed and implemented to reduce mother-to-child transmission of syphilis. Its value helps to identify at-risk groups in need of improved prenatal care and surveillance for the disease, analyze temporal and geographical trends, and estimate human, economic, and technological resources to strengthen preventive programs.

This indicator is part of the Monitoring Framework for Universal Health in the Americas, measuring national progress on implementing policies aimed at strengthening health systems and achieving universal health. It is part of efforts to monitor the progress of countries eliminating mother-to-child transmission of syphilis.

As a shared target exists to eliminate mother-to-child transmission of HIV and congenital syphilis, WHO, UNICEF, and UNAIDS provide joint support to assess congenital syphilis incidence and include it in the Progress Report on the Global Response to HIV/AIDS.

The value of this indicator comes from cases reported by countries to the World Health Organization (WHO), collected in their routine health information systems.

The numerator is the number of reported congenital syphilis cases (live births and stillbirths) in the previous 12 months in a specific country, territory, or geographical area. The populations used in the denominator are from estimates by the United Nations Population Division. The incidence is calculated by PAHO.

Formula:
(A/B) x 1 000

Numerator (A):
Number of reported cases of congenital syphilis in year z in a given country, territory, or geographic area.

Denominator (B):
Number of live births in year z in a country, territory, or geographic area.

The incidence of congenital syphilis in country A reached 1.5 per 1 000 live births in 2019, i.e., per 1 000 live births, 1.5 new cases of congenital syphilis were reported that year.

No disaggregation

There are several limitations on this indicator, one of the most important being low availability of specific diagnostic tests. In many countries, congenital syphilis is diagnosed based on medical history and physical examination. This affects diagnostic reliability and the accuracy of the indicator.

Possible differences between WHO and the countries regarding their operational definitions of congenital syphilis can be a factor. Although WHO has a global definition for surveillance purposes, the actual definition may vary within or between countries.

World Health Organization (WHO). The Global Health Observatory (GHO). Available from:
https://www.who.int/data/gho/indicator-metadata-registry

Annual

Pan American Health Organization. Strategic Plan of the Pan American Health Organization 2020-2025.
Indicator: 18. Incidence rate of congenital syphilis (including stillbirths)
Available from: https://www.paho.org/en/documents/paho-strategic-plan-2020-2025

Pan American Health Organization (PAHO). Monitoring Framework for Universal Health in the Americas. Washington, D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/53918

World Health Organization (WHO). Methods for surveillance and monitoring of congenital syphilis elimination within existing systems. Geneva, 2011. Available from: https://www.who.int/reproductivehealth/publications/rtis/9789241503020/en/

World Health Organization (WHO). Global guidance on criteria and processes for validation: elimination of mother-to-child transmission of HIV and syphilis. Geneva, 2017. Available from: https://www.paho.org/en
ode/21360


World Health Organization (WHO). Global health sector strategy on Sexually Transmitted Infections, 2016-2021. Towards ending STIs. Geneva, 2016. Available from: https://www.paho.org/en/documents/global-health-sector-strategy-sexually-transmitted-infections-2016-2021-towards-ending#:~:text=The%20present%20global%20health%20sector,goals%2C%20targets%2C%20guiding%20principles%20and

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho/indicator-metadata-registry

Mortality

Child health

The quotient between the total number of deaths in children under 1 year of age in a given country, territory, or geographic area during a specific calendar year and the number of live births in the same population and year, expressed per 1 000 live births.

Live birth means the complete expulsion or extraction from its mother of a product of conception, irrespective of the duration of pregnancy, that, after such expulsion or extraction, breathes or shows any other evidence of life, such as beating of the heart, pulsation of the umbilical cord, or definite movement of voluntary muscles, whether or not the umbilical cord has been cut or the placenta is attached. Each product of such childbirth that meets these conditions is considered a live birth. (ICD-10)

1 000 live births

Rate

Crude/Corrected

This indicator quantifies infant deaths as a public health problem for a given population or geographic area. The value reflects the risk of children born alive dying during their first year of life. It makes it possible to identify health inequities and populations with specific risk factors.

The infant mortality rate reflects children’s health status and social, economic, and environmental conditions. It is related to maternal and child health care access, quality, and timeliness. Its applications include strengthening professional childbirth care, breastfeeding, and vaccination programs.

This indicator is useful for designing, implementation, and evaluation of health policies and the distribution of economic, human, and technological resources aimed at improving maternal and child health. Its applications include evaluating time and geographic trends in infant mortality.

The infant mortality rate uses infant deaths reported by the national health agency as the numerator and the total number of live births for the same population and year as the denominator.

Formula:
(A/B) x 1 000

Numerator (A):
Number of infant deaths in year z in a given country, territory or geographic area

Denominator (B):
Total number of live births in year z in the same country, territory or geographic area

To estimate the indicator by sex, the following formula is applied:
(A/B) x 1 000

Numerator (A):
Number of infant deaths of a given sex in year z in a specific country, territory, or geographic area.

Denominator (B):
Total number of live births of the same sex in year z in the same country, territory, or geographic area.

The infant mortality rate of country A for 2019 was 8.3 per 1 000 live births; that is, in that year eight children died before the age of 1 per 1 000 live births in country A.

By sex

The infant mortality rate requires a civil registry system with good coverage, and births and deaths must be recorded in a timely manner in this system; otherwise, this indicator will not be sufficiently accurate.

The value of this indicator may differ from each country’s value due to methodological differences such as the application of algorithms to reassign ill-defined causes of death and methods to correct underreporting of births and deaths.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

ICD-10, International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Vol 2. Available from: https://icd.who.int/browse10/Content/statichtml/ICD10Volume2_en_2010.pdf

Sociodemographic

Socioeconomic

Inflation, as measured by the consumer price index, reflects the annual percentage change for an average consumer in the cost of purchasing a basket of goods and services that can be fixed or changed at specific intervals (e.g., annually) for a given national economy. To calculate the consumer price index, the Laspeyres formula is usually used.

Percentage

Proportion

Corrected

Because inflation translates the increase in prices of goods and services, it is used to evaluate consumers' purchasing power in a given national economy and how it evolves over time.

It is one of the indicators used by central banks to set monetary policies, such as interest rates. Analysis of its value includes identifying whether the observed change is due to an increase in demand, the cost of raw materials, or the money supply, among other factors, and implementing measures aimed at controlling it.

Inflation is closely related to a country's fiscal policies, deficit, and unemployment level.

The consumer price index is generally explicitly derived as the weighted arithmetic average of the current prices of goods and services in the fixed basket, obtained through recurring price surveys, according to their weights based on fixed values for the base period (Laspeyres formula), which are also obtained from household expenditure surveys. The growth rates of the consumer price index are estimated by the World Bank from the corresponding data provided by the United Nations System of National Accounts and using the least squares method.

The cumulative inflation of country A in 2019 was 3.2%. This means the average price of goods and services included in the basic basket of this country rose by 3.2% compared to the previous year.

No disaggregation

Inflation is estimated based on the percentage change in the consumer price index, which measures the average cost of goods and services included in the basic household basket. The makeup of the household basket varies between countries and is subject to the income and consumption patterns of its inhabitants. When based on a survey, the accuracy of this indicator depends on the quality of the data obtained from the survey. Products sold in informal trade are not considered when calculating the consumer price index.

The frequency with which countries update their data and transfer it to the World Bank for calculation affects the result of this indicator.

World Bank. Open Data & Databank. World Development Indicators. Available from: https://data.worldbank.org/indicator

For the most recent data, see the primary source (World Bank).

Not applicable

World Bank Open Data. Available from: https://data.worldbank.org/

Mortality

Cause of death

Proportion of injury deaths during a specific calendar year, in the population in a certain country or geographic area, in relation to total estimated deaths for the same place and year. Expressed as a percentage.

Percentage

Proportion

Corrected

The proportion of injury deaths helps to quantify the relative importance of this group of pathologies in the mortality of a given population or geographic area.

The value of this indicator is related to the quality of health care provided for this type of event and the identification of higher-risk populations and geographic areas, suggesting the need for more detailed analysis.

Its result is applicable in the design, implementation, and evaluation of health, transportation, and public safety policies related to injury deaths and in the distribution of economic, human, and technological resources for the prevention of injury deaths, among others.

To estimate the percentage of injury deaths, the number of deaths from this group of conditions is used as the numerator and the total number of deaths from all causes as the denominator.
The underlying causes of death correspond to International Classification of Diseases, Tenth Revision (ICD-10) codes V01 - Y89 (except X41 - X42, X44 - X45).

Data for this indicator are from the World Health Organization (WHO) Global Health Estimates (GHE), based on information from multiple sources, such as national civil registry systems, estimates from WHO technical programs, the United Nations and inter-agency groups, the Global Burden of Disease, and other scientific studies.

By applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death. For countries without high-quality death registration data, cause of death estimates is calculated using other data, for example, household surveys with verbal autopsy, sentinel registry systems, or special studies.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://cdn.who.int/media/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods.pdf?sfvrsn=37bcfacc_5

According to 2019 data, 5.4% of the deaths in country A were from injuries; that is, five out of every 100 deaths in that country were a result of some type of injury.

By sex

The estimated value of this indicator may differ from each country’s calculations due to differences such as the use of a different group of ICD-10 codes or the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Calculating the proportion of injury deaths requires a civil registry system with good coverage. Deaths from this group of causes must be recorded in that system in a timely manner and certification of cause of death must be of good quality. This must include reporting deliberate acts resulting in death; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from:
https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from:
https://www.who.int/data/gho/indicator-metadata-registry

World Health Organization (WHO). Global status report on road safety 2018. Geneva, 2018. Available from: https://www.who.int/publications/i/item/9789241565684

Mortality

Cause of death

The estimated total number of deaths from ischemic heart diseases in the population, in a given country, territory or geographic area during a specific calendar year, divided by the total number of this population, generally estimated in the middle of the same year (1 July), after removing the effect of differences in the age distribution of the population. Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected

This indicator reflects the health status and socio-economic development of a population and makes it possible to identify populations at greater risk of dying from ischemic heart diseases and to encourage research in this area.

Its result is applicable to the design, implementation, and evaluation of health policies on ischemic heart diseases and the distribution of economic, human, and technological resources for the prevention, diagnosis, treatment, and control of this group of pathologies, among others. Its applications include, for example, evaluating over time the effectiveness of interventions to promote healthy lifestyles or myocardial revascularization.

The age-adjusted ischemic heart diseases mortality rate allows for the comparison of this indicator across populations or in the same population over time.

The numerator of this indicator uses deaths from ischemic heart diseases, from the World Health Organization (WHO) Global Health Estimates (GHE). These estimates are based on data from multiple sources, such as national civil registry systems, estimates from WHO technical programs, the United Nations and inter-agency groups, and the Global Burden of Disease, among others.

The underlying causes of death correspond to codes I20 – I25 of the International Classification of Diseases, Tenth Revision (ICD-10).

The populations used in the denominator of the age-adjusted ischemic heart diseases mortality rate are from estimates by the United Nations Population Division.

Applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as garbage codes.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The ischemic heart diseases mortality rate is adjusted for age by direct standardization, applying estimated age-specific mortality rates, for both sexes or for a given sex, to the World Health Organization (WHO) World Standard Population.

The age-adjusted ischemic heart diseases mortality rate for 2019 was 83 per 100 000 population in country A and 38 per 100 000 population in country B; that is, in 2019 ischemic heart diseases were responsible for the death of 83 people per 100 000 population in country A, compared to country B, where 38 people died from the same group of causes per 100 000 population. This means that, in 2019, the population of country A had a higher risk of dying from ischemic heart diseases than in country B.

By sex

The age-adjusted ischemic heart diseases mortality rate is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

The estimated value of the age-adjusted ischemic heart diseases mortality rate will depend on the standard population used for its adjustment; therefore, it may differ from each country’s estimates. Other methodological considerations that influence its result are the use of a different group of ICD-10 codes and the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Estimating the ischemic heart diseases mortality rate requires a civil registry system with good coverage. Deaths from ischemic heart diseases must be recorded in a timely manner in that system, and certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Sociodemographic

Socioeconomic

The ratio of the total cumulative income of the richest 20% of households (quintile 5) to the total cumulative income of the poorest 20% (quintile 1), ordered according to the distribution of household per capita income in a given population and over a specific period, usually one year.

 

Ratio

Corrected

The Kuznets index is used to measure inequality in a country's income distribution; this inequality is reflected in the proportion of income held by a part of the population classified by income level.

Along with other macroeconomic indicators, such as the Gini coefficient, the Kuznets index is used to analyze changes in a country's economic inequality over time. It is used to design socioeconomic policies to address poverty.

The Kuznets ratio is calculated by PAHO based on estimates made by the World Bank according to data on income distribution or consumption from nationally representative household surveys. When original household survey data are available, they are used to directly calculate the share of income or consumption per quintile. If the original data are not available, figures are estimated from the best available pooled data. Distribution data are adjusted for household size, providing a more consistent measure of per capita income or consumption.

Formula:
(A/B) x 100

Numerator (A):
Total income of the richest quintile

Denominator (B):
Total income of the richest quintile

No adjustments are made for spatial differences in the cost of living within countries, because the data needed for such calculations are generally not available.

According to 2019 data, the Kuznets index of country A was 10.9. This means that the income of the highest income households (quintile 5) is almost 11 times that of the lowest income households (quintile 1).

No disaggregation

The accuracy of this indicator depends on the timeliness, frequency, quality, and comparability of household surveys. The availability of data from these surveys affects use of this indicator to monitor poverty.

Low frequency and lack of comparability among surveys due to methodological differences are other factors that hinder monitoring poverty.

The frequency with which countries update their data and transfer it to the World Bank for calculation affects the result of this indicator.

World Bank. Open Data & Databank. World Development Indicators. Available from: https://data.worldbank.org/indicator

For the most recent data, see the primary source (World Bank).

Not applicable

World Bank Open Data. Available from: https://data.worldbank.org/

Morbidity

Communicable diseases

Number of leprosy cases registered for treatment (reported leprosy prevalence) as of 31 December of a given year in a specific country, territory, or geographical area.

Cases

Magnitude

Crude

Leprosy (Hansen disease) is a chronic infectious disease caused by Mycobacterium leprae. It mainly affects the skin, peripheral nerves, upper respiratory tract mucosa, and eyes. Despite its severity, the disease can be cured through multi-drug treatment. If treated in the early stages, all types of leprosy can be cured, and the associated disability prevented.

This indicator is used to monitor disease elimination. It helps identify vulnerable populations in need of strengthened national surveillance systems, improve detection among those affected, ensure treatment, and intensify leprosy elimination campaigns in line with the Global Leprosy (Hansen disease) Strategy 2021–2030.

Leprosy was eliminated globally as a public health problem (defined as a recorded prevalence of less than 1 case per 10 000 pop) in 2000.

The data is primarily collected from national surveillance systems that regularly report to the Pan American Health Organization.

In country A, there were two cases of leprosy registered for treatment in 2019.

By sex

This indicator depends on the effectiveness and coverage of national leprosy surveillance systems, as well as early detection and timely treatment.

National health authority

Annual

Not applicable

Towards zero leprosy. Global leprosy (Hansen's disease) strategy 2021–2030. Available from: https://www.who.int/publications/i/item/9789290228509

WHO. Weekly Epidemiological Record. Global leprosy (Hansen disease) update, 2020: impact of COVID-19 on global leprosy control. Available from: https://www.who.int/publications/i/item/who-wer9636-421-444

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho/data/themes/topics/leprosy-hansens-disease

World Health Organization (WHO). Elimination of leprosy as a public health problem. Resolution WHA51.15. May 1998. Available from: https://apps.who.int/iris/handle/10665/79814

Morbidity

Communicable diseases

The number of registered cases of leptospirosis in the population of a given country, territory, or geographic area in one year. It includes cases of leptospirosis with clinical or epidemiological suspicion, as well as laboratory-confirmed cases.

Cases

Magnitude

Crude

Leptospirosis is a zoonotic disease caused by spirochetes of the genus Leptospira, which can cause clinical pictures with different degrees of organ involvement and even death. It has a worldwide distribution and is endemic mainly in countries with humid tropical or subtropical climates that have epidemic potential. In addition to humans, it affects several species of domestic and wild mammals, which are its reservoir. Occasionally, outbreaks associated with the ingestion of contaminated water or food may occur. Early detection and administration of antibiotics allows the disease to be treated successfully.

The number of cases of leptospirosis makes it possible to quantify the magnitude of this disease in the population, analyze its temporal and geographic trend, and identify areas and groups at greatest risk for transmission. This indicator contributes to the design and evaluation of strategies for the prevention and control of leptospirosis in the community and to the allocation of resources to control it.

The number of cases of leptospirosis is from data officially reported to the Pan American Health Organization (PAHO) by the Ministries of Health of the affected countries. These data are mostly collected through leptospirosis surveillance systems and national technical programs.

Country A had 95 registered cases of leptospirosis in 2019.

By sex

This indicator’s value depends on the coverage and performance of surveillance systems and the coordination of efforts across the multiple sectors involved in addressing leptospirosis. One of the main factors affecting the accuracy of this indicator is that leptospirosis is not reported in many countries due to the difficulty of clinical diagnosis and the lack of laboratories to diagnose it. Another element to consider is that its multiple clinical manifestations result in a low diagnostic suspicion and, consequently, an undercount of cases.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). PLISA Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators
World Health Organization (WHO). The Global Health Observatory (GHO). Available from:
https://www.who.int/data/gho/indicator-metadata-registry

World Health Organization (WHO). Human leptospirosis: guidance for diagnosis, surveillance, and control. Geneva, 2003. Available from:
https://apps.who.int/iris/handle/10665/42667

Sociodemographic

Demographic

The average number of years that a newborn is expected to live, as a member of a hypothetical birth cohort, if exposed to the age- and sex-specific mortality rates prevailing at birth, for a specific year, in a given country, territory, or geographic area.

Years

Index

Corrected/Predicted

Life expectancy at birth reflects the overall mortality level of a population. It reflects the intensity of mortality in different age groups for the same calendar year and geographical location as well as the living and health conditions of a population.

Unlike the crude mortality rate, it is independent of the population's age structure, which allows comparisons to be made between different populations and within the same population over time.

The value of this indicator comes from United Nations estimates, based on data representing estimated mid-year values, obtained by linear interpolation of the corresponding United Nations five-year medium-variant population projections.

Life tables are used in the multi-step calculation of life expectancy at birth, based on age- and sex- specific mortality rates. Their values represent mid-year estimates.

The life expectancy of country A in 2018 was 75.8 years. This means that, if the age-specific mortality rates observed in 2018 did not change, people born that year in the country would live an average of 75.8 years.

By sex

Life expectancy is a hypothetical measure whose calculation is based on national mortality rates. Therefore, it depends on the quality of information sources used to develop life tables as inputs to calculate life expectancy at birth.

Whenever vital records systems with full coverage are not available or the accuracy of the data is inadequate, life expectancy at birth should be estimated using indirect demographic methods, applicable to large geographical areas.

Life expectancy at birth may differ depending on the method used to draw up the life table.

Life expectancy changes as a person ages, changing according to potential shifts in mortality trends and the health conditions of the population in which they live.

United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects. Available from:
https://population.un.org/wpp/

Annual

Pan American Health Organization. Strategic Plan of the Pan American Health Organization 2020-2025.
Indicator 2. Health-adjusted life expectancy (HALE)
Available from: https://www.paho.org/en/documents/paho-strategic-plan-2020-2025

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from:
https://www.who.int/data/gho/indicator-metadata-registry

United Nations, Department of Economic and Social Affairs. 2019 Demographic Yearbook, 70th Issue. New York, 2020. Available from: https://unstats.un.org/unsd/demographic-social/products/dyb/

United States Census Bureau. International Database. Glossary. Available from: https://www.census.gov/glossary/

United Nations, Department of Economic and Social Affairs, Population Division. Glossary of Demographic Terms. Available from:
https://population.un.org/wpp/GlossaryOfDemographicTerms/

Economic Commission for Latin America and the Caribbean (ECLAC) - CEPALSTAT. Statistical Databases and Publications. Available from:
https://statistics.cepal.org/portal/cepalstat/dashboard.html?lang=en

Pan American Health Organization. Basic Health Indicators in Brazil: concepts and applications, 2nd edition. Brasilia, 2008. Available from: https://www.paho.org/bra/dmdocuments/indicadores.pdf

Haupt, A., Kane, T., Haub C. Population Reference Bureau’s Population Handbook (Sixth Edition) Washington, D.C. 2011. Available from: https://www.prb.org/population-handbook/

Risk factor

Child health

Percentage of live births with a birth weight of less than 2 500 grams (up to and including 2 499 grams), compared to the total number of live births, in the same country, territory, or geographical area and year. Expressed per 100 live births.

The newborn’s weight measured for the first time after birth is known as birth weight. With live births, birth weight should be taken during the first hour of life, before significant postpartum weight loss occurs.

Percentage

Proportion

Crude

The percentage of live births with low birth weight reflects the health status of a population. It is associated with maternal malnutrition and poor medical care during pregnancy, among other factors, and is an important predictor of fetal mortality and newborn health and survival. In later stages, it is associated with impaired cognitive development and noncommunicable diseases, such as diabetes mellitus or cardiovascular diseases.

This indicator is related to the quality of maternal and child health care and social vulnerability. It allows at-risk populations to be identified and focuses strategies to strengthen access to timely and quality health and nutritional interventions. Research is incentivized to identify risk factors for low birth weight and propose appropriate interventions.

The percentage of low-weight newborns is part of the indicators of the Global Nutrition Monitoring Framework on Maternal, Infant, and Young Child Nutrition. These indicators monitor progress made by countries towards global nutrition targets. They also allow monitoring of the Monitoring Framework for Universal Health in the Americas, to measure national progress on implementing policies aimed at strengthening health systems and achieving universal health.

The percentage of newborns with low birth weight is provided by national health agencies to the Pan American Health Organization (PAHO), based on information sources that vary depending on the situation of each country, including national health information systems, national vital statistics, demographic and health surveys (DHS), and health services or facilities records, among other sources.

Formula:
(A/B) x 100 live births

Numerator (A):
Number of live newborns with birth weight lower than 2 500 g, in a given country, country, territory, or geographical area and year.

Denominator (B):
Total number of live births in the same country and year.

According to 2019 data, the percentage of low birth weight in country A is 9.8%, which means, of every 100 live births in this country, 10 have a birth weight of less than 2 500 g.

No disaggregation

The accuracy of this indicator depends on the quality of the data used for calculations and the availability of information sources. The fact that a high percentage of newborns are not weighed at birth is a major limiting factor. It’s also worth noting that calculations require timely recording of live births in a system with adequate coverage.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO). Monitoring Framework for Universal Health in the Americas. Washington D.C. 2021. Available from:
https://iris.paho.org/handle/10665.2/53918

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho/indicator-metadata-registry

World Health Organization (WHO). Indicators for the Global Monitoring Framework on Maternal, Infant and Young Child Nutrition, 2014. Available from:
https://www.who.int
ews-room/events/detail/2014/11/24/default-calendar/indicators-for-the-global-monitoring-framework-on-maternal-infant-and-young-child-nutrition

World Health Organization (WHO). Maternal, infant and young child nutrition, March 2018. Available from:
https://apps.who.int/gb/ebwha/pdf_files/WHA71/A71_22-en.pdf

UNICEF Data: Monitoring the situation of children and women. Available from: https://data.unicef.org/

Mortality

Cause of death

The estimated total number of deaths from lower respiratory infections in the population in a given country, territory or geographic area during a specific calendar year, divided by the total number of this population, generally estimated in the middle of the same year (1 July), after removing the effect of differences in the age distribution of the population. Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected

This indicator reflects a population’s health status and makes it possible to identify those with greater risk factors for dying from lower respiratory infections and to encourage research in this area.

Its result is applicable to the design, implementation, and evaluation of health policies on lower respiratory infections and the distribution of economic, human, and technological resources for the prevention, diagnosis, treatment, and control of this group of pathologies, among others. Its applications include, for example, analyzing the effect of immunoprevention interventions and strategies for promoting healthy lifestyles on mortality from lower respiratory infections.

Adjusting for age allows for the comparison of this indicator across populations or in the same population over time.

The numerator of this indicator uses deaths from lower respiratory infections, from the World Health Organization (WHO) Global Health Estimates (GHE). These estimates are based on data from multiple sources, such as national civil registry systems, estimates from WHO technical programs, the United Nations and inter-agency groups, and the Global Burden of Disease, among others.

The underlying causes of death correspond to codes J09 - J22, P23, U04 of the International Classification of Diseases, Tenth Revision (ICD-10).

The populations used in the denominator of the age-adjusted lower respiratory infection mortality rate are from estimates by the United Nations Population Division.

Applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as garbage codes.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The lower respiratory infection mortality rate is adjusted for age by direct standardization, applying estimated age-specific mortality rates, for both sexes or for a given sex, to the World Health Organization (WHO) World Standard Population.

The age-adjusted lower respiratory infection mortality rate for 2019 was 25 per 100 000 population in country A and 12 per 100 000 population in country B; that is, in 2019 lower respiratory infections were responsible for the death of 25 people per 100 000 population of country A, compared to country B, where 12 people died from the same group of causes per 100 000 population. This means that, after removing the effect of differences in the age distribution between the two countries, the risk of dying from lower respiratory infections in 2019 was higher in the population of country A than in country B.

By sex

The age-adjusted lower respiratory infection mortality rate is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

The estimated value of the age-adjusted lower respiratory infection mortality rate will depend on the standard population used for its adjustment; therefore, it may differ from each country’s estimates. Other methodological considerations that influence its result are the use of a different range of ICD-10 codes and the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Estimating the lower respiratory infection mortality rate requires a civil registry system with good coverage. Deaths must be recorded in a timely manner in that system, and certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Morbidity

Cancer

The ratio of new cases of trachea, bronchial, and lung cancer (ICD-10 codes: C33 - C34) arising in a given country, territory, or geographical area during a specific period (usually one year), to the total population of the same country and year. This indicator is age-standardized to control for the effect of different age structures.

Per 100 000 population

Rate

Predicted

Alongside mortality and prevalence estimates, lung cancer incidence rates provide a comprehensive assessment of the impact of the disease in 185 countries or territories, including the Region of the Americas.

The data used to estimate this indicator come from cancer registries that identify new cases occurring in a well-defined population, generating statistics to evaluate and control the impact of these diseases in the population.

The age-adjusted trachea, bronchial, and lung cancer incidence rate provides an estimate of the average risk the population has of developing these types of cancer in a particular country, territory, or geographic area. Its results are used to planning and allocating economic, human, and technological resources to fight lung cancer. It can be applied, for example, to evaluate the effectiveness of smoking restrictions.

As the trachea, bronchial, and lung cancer incidence rate is age-adjusted, comparisons can be made both within and between populations over time. It helps to identify at-risk groups, determine the presence of specific risk factors for different groups, and assess timely access to diagnosis and treatment.

This indicator supports public policy-making and is essential for planning and evaluating trachea, bronchial, and lung cancer screening, early diagnosis, treatment, and control programs. It helps to focus efforts such as identifying the need to strengthen and implement cancer registries in a given population.

Data for this indicator come from national or subnational population cancer registries that are routinely maintained in the Global Cancer Observatory (GCO) 2020: Cancer Incidence in Five Continents (CI5) database.

The methods used to estimate the trachea, bronchial, and lung cancer incidence rate in a specific country depend on the available data sources. These include projections of observed incidence rates at the national level, statistical models derived from incidence rates in the country's cancer registries or neighboring country registries, and average incidence rates in neighboring countries, among other metrics.

The trachea, bronchial, and lung cancer incidence rate is age-standardized and results are based on rates in populations with a standard age structure.

The age-standardized rate is a summary measure of the rate that would have been observed in a population with a standard age structure. Standardization is necessary when comparing several populations that differ in age, as age is a major factor when determining cancer risk. An age-standardized rate is a weighted average of age-specific rates based on a standard population distribution.

In 2019, the lung cancer incidence rate in country A was 24.8 per 100 000 pop. In country B, it was 48.9 per 100 000. In other words, the probability of developing lung cancer in country A in 2019 was 24.8 per 100 000 pop. The risk of developing these types of cancer in country B is twice as high as in country A.

By sex

The data presented at the Global Cancer Observatory are the best available for each country. However, the indicator should be interpreted with caution considering current limitations in the quality and coverage of cancer data, particularly in low- and middle-income countries.

In addition, the age-adjusted trachea, bronchial, and lung cancer incidence rate is not a real value. Its main purpose is to allow comparisons over time between different populations or within the same population. It reflects the average risk of developing these types of cancer in a particular country. This should not be interpreted as the individual risk of developing these cancers.

The estimated value of the age-adjusted trachea, bronchial, and lung cancer incidence rate depends on the standard population used for its adjustment; it may therefore differ from the calculations made by each country.

Global Cancer Observatory (GCO). Cancer Incidence in Five Continents (CI5). Available from: https://ci5.iarc.fr/CI5plus/Default.aspx

Annual

Not applicable

International Agency for Research on Cancer (IARC), CANCER TODAY. Available from: https://gco.iarc.fr/today/home

Bray F, Colombet M, Mery L, Piñeros M, Znaor A, Zanetti R, Ferlay J, editors (2021). Cancer Incidence in Five Continents, Vol. XI. IARC Scientific Publication No. 166. Lyon: International Agency for Research on Cancer. Available from:
https://publications.iarc.fr/597

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Global Reference List of 100 Core Health Indicators (plus health-related SDGs). Available from: https://apps.who.int/iris/handle/10665/259951

Mortality

Cause of death

The estimated total number of deaths from cancer of the trachea, bronchus and lung in the population, in a given country, territory, or geographic area during a specific calendar year, divided by the total number of this population, generally estimated in the middle of the same year (1 July), after removing the effect of differences in the age distribution. Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected

This indicator helps to identify populations at higher risk of dying from cancer of the trachea, bronchus and lung and to assess the presence of risk factors, such as those associated with environment or lifestyle.

Its result is applicable to the design, implementation, and evaluation of health policies for the prevention and control of cancer of the trachea, bronchus and lung and the distribution of economic, human, and technological resources for this disease, among others. Its applications include, for example, evaluating the effectiveness of smoking restriction measures in closed spaces.

Removing the effect of a different age distribution by using a standard population makes it possible to analyze the time trend and geographic distribution of deaths from cancer of the trachea, bronchus and lung, in the same population or across populations.

The numerator of this indicator uses deaths from cancer of the trachea, bronchus and lung from the World Health Organization (WHO) Global Health Estimates (GHE). These estimates are based on data from multiple sources, such as national civil registry systems, estimates from WHO technical programs, the United Nations and inter-agency groups, and the Global Burden of Disease, among others.

The underlying causes of death correspond to codes C33 – C34 of the International Classification of Diseases, Tenth Revision (ICD-10).

The populations used in the denominator of the mortality rate from cancer of lung are from estimates by the United Nations Population Division.

Applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as garbage codes.
For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The mortality rate from cancer of lung is adjusted for age by direct standardization, applying estimated age-specific mortality rates, for both sexes or for a given sex, to the World Health Organization (WHO) World Standard Population.

The age-adjusted lung cancer mortality rate for 2019 is 18 per 100 000 population in country A and 11 per 100 000 population in country B; that is, in that year 18 people died from cancer of the trachea, bronchus and lung per 100 000 population of country A, compared to country B, where 11 people died from that cause per 100 000 population. This means that, after removing the effect of differences in the age structure in the two countries, the population of country A had a higher risk of dying from lung cancer in 2019.

By sex

The age-adjusted mortality rate is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

The estimated value of the age-adjusted mortality rate from cancer of the lung will depend on the standard population used for adjustment.

The estimated value of this indicator may differ from each country’s estimates due to methodological considerations such as the method used to prepare the population estimates and projections, the use of a different range of ICD-10 codes, or the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Estimating the mortality rate from cancer of the lung requires a civil registry system with good coverage. Deaths must be recorded in this system in a timely manner, and certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Morbidity

Communicable diseases

Number of confirmed cases of malaria in a given year in a specific country, territory, or geographical area.

A case of malaria is defined as the presence of malarial parasite infection in a person's blood, confirmed by diagnostic examination.

Cases

Magnitude

Crude

Malaria is an often-deadly parasitic disease, borne by female Anopheles mosquitoes. Despite the associated risk, especially for children, the disease is preventable and curable. Prevention is based on anti-vector measures, such as insecticide-treated nets and intra-household residual spraying, and prophylactic treatment, only in case of travel to an endemic area, because it can stop the infection in its blood stage, preventing the disease. The second pillar of malaria control is early diagnosis and treatment to reduce incidence, prevent deaths, and contribute to reducing transmission.

This indicator is used to monitor countries progressing towards targets established in the Global Technical Strategy for Malaria 2016–2030. It also contributes to monitoring national progress on the objectives of the Monitoring Framework for Universal Health in the Americas.

The indicator makes it possible to assess the temporal and geographical trends of malaria and identify at-risk populations in need of strengthened surveillance programs, malaria elimination activities, and access to interventions, especially integrated and quality diagnosis and treatment. The value of the indicator is considered when allocating economic, human, and technological resources.

In the Americas, there are 18 endemic countries and territories (as of 2021):
Belize, Bolivia, Brazil, Colombia, Costa Rica, Dominican Republic, Ecuador, French Guiana, Guatemala, Guyana, Haiti, Honduras, Mexico, Nicaragua, Panama, Peru, Suriname, and Venezuela.

The number of cases in malaria-endemic countries is collected from each country's surveillance system. This information is reported annually to the World Health Organization in the World Malaria Report.

Information from non-endemic countries is reported directly to PAHO/WHO and classified as 'imported'.

Imported cases are transmitted by mosquitoes and contracted outside the area where diagnosis took place, in an area known to have malaria transmission, or areas visited by the patient outside the elimination zone.

In country A, there were 15 cases of malaria in 2019.

By sex

The value of this indicator is impacted by the effectiveness of surveillance systems, which in turn may be affected by low diagnostic suspicion and underreporting of cases, the availability of laboratory tests for diagnosis, and whether private health centers report identified cases.

National health authority

Annual

United Nations (UN). Department of Economic and Social Affairs.
Sustainable Development Goals (SDG)
Indicator 3.3.3: Malaria incidence per 1 000 population
Available from: https://sdg.data.gov/

Pan American Health Organization. Strategic Plan of the Pan American Health Organization 2020-2025.
Indicator 21. Incidence rate of malaria
Available from: https://www.paho.org/en/documents/paho-strategic-plan-2020-2025

Pan American Health Organization (PAHO). Malaria surveillance, monitoring & evaluation: a reference manual. Washington, D.C., 2018. Available from: https://iris.paho.org/bitstream/handle/10665.2/50648/9789275320563_spa.pdf?ua=1

World Health Organization (WHO). The Seventy-fourth World Health Assembly. Recommitting to accelerate progress towards malaria elimination. Draft Resolution A74/B/CONF./2. May 2021. Available from: https://apps.who.int/gb/ebwha/pdf_files/WHA74/A74_BCONF2-en.pdf

World Health Organization (WHO). WHO malaria terminology. Geneva, 2022. Updated in November 2021. Available from: https://www.who.int/publications/i/item/9789240038400

Global Technical Strategy for Malaria 2016–2030. Available from: https://www.paho.org/en/documents/global-technical-strategy-malaria-2016-2030

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho/indicator-metadata-registry

Pan American Health Organization (PAHO). Monitoring Framework for Universal Health in the Americas. Washington, D.C.; 2021. License: CC BY-NC-SA 3.0 IGO. Available from: https://iris.paho.org/handle/10665.2/53918

Mortality

Cause of death

The estimated total number of deaths from malignant neoplasms in the population, in a given country, territory, or geographic area during a specific year, divided by the total number of this population, generally estimated in the middle of the same year (1 July), after removing the effect of differences in the age distribution. Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected

This indicator helps to identify populations at higher risk of dying from malignant neoplasms and to evaluate the presence of potential risk factors, such as those associated with diet, environment, or lifestyle.

Its result is applicable to the design, implementation, and evaluation of health policies for the prevention and control of malignant neoplasms and the distribution of economic, human, and technological resources, among others. Its applications include evaluating screening and early diagnosis strategies over time.

Removing the effect of differences in the age distribution by using a single standard population makes it possible to analyze the time trend and geographic distribution of deaths from malignant neoplasms in the same population or across populations.

The numerator of this indicator uses deaths from malignant neoplasms from the World Health Organization (WHO) Global Health Estimates (GHE) and the civil registry and national vital statistics systems of the countries in the Region of the Americas.

The underlying causes of death correspond to codes C00 – C97 of the International Classification of Diseases, Tenth Revision (ICD-10).

The populations used in the denominator of the malignant neoplasms mortality rate are from estimates by the United Nations Population Division.

Applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as garbage codes.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The malignant neoplasms mortality rate is adjusted for age by direct standardization, applying estimated age-specific mortality rates, for both sexes or for a given sex, to the World Health Organization (WHO) World Standard Population.

The age-adjusted malignant neoplasms mortality rate for 2019 is 12 per 100 000 population in country A and 6 per 100 000 population in country B; that is, in country A 12 people died from a malignant neoplasm per 100 000 population, compared to country B, where six died per 100 000 population. This means that, after removing the effect of differences in the age structure in the two countries, the risk of dying from malignant neoplasms in 2019 was higher in country A.

By sex

The age-adjusted malignant neoplasms mortality rate is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

Due to the application of advanced statistical models, estimates may differ from each country’s results. The estimated value of the age-adjusted malignant neoplasms mortality rate will depend on the standard population used for its adjustment; therefore, it may differ from each country’s estimates. Other methodological considerations that influence its result are the use of a different range of ICD-10 codes and the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Estimating the malignant neoplasms mortality rate requires a civil registry system with good coverage. Deaths must be recorded in a timely manner in this system, and certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Mortality

Maternal and reproductive health

The ratio between the number of maternal deaths and the number of live births in a given country, territory, or geographical area in a specific calendar year. Expressed per 100 000 live births.

Maternal death is defined as the death of a woman while pregnant or within 42 days following termination of pregnancy, regardless of the duration and anatomical site of the pregnancy, related to or aggravated by pregnancy or its management (excluding accidental or incidental causes) (ICD-10).

Live birth refers to the complete expulsion or extraction from its mother of a product of conception, regardless of the duration of the pregnancy, which, after such separation, breathes or shows any other evidence of life, (e.g., beating heart, pulsating umbilical cord, or definite movement of voluntary muscles) whether or not the umbilical cord has been cut or the placenta is attached. Each product of such childbirth that meets these conditions is considered as a live birth. (ICD-10)

100 000 live births

Ratio

Crude/Corrected

Maternal mortality (SDG 3.1) remains a high priority on the world's health agenda.

The maternal mortality ratio reflects the magnitude of maternal mortality, increases its visibility as a serious public health problem, and contributes to raising societal awareness about the issue. It reflects a population's state of health, as well as its socioeconomic and health development. It allows inequities in health and higher-risk populations to be identified, and highlights the need to focus economic, human, and technological resources to respond appropriately to deficiencies detected.

Its value reflects the risk that a woman has of dying from complications related to pregnancy, childbirth, or the postpartum period, and encourages research in maternal and child issues.

This indicator is associated with access to and quality of women's health care, including family planning, antenatal care, attendance at childbirth, and the postpartum period. It identifies the need for specialized health personnel to prevent and treat complications that occur during pregnancy and childbirth.

Measurement of maternal mortality requires information on pregnancy status, time of death (during pregnancy, childbirth, or within 42 days of termination of pregnancy), and cause of death.

The maternal mortality ratio is calculated using as a numerator the deaths of women occurring during pregnancy, childbirth, or the postpartum period, reported by the national health authority of a given country, territory, or geographical area in a specific calendar year, and as denominator the total number of live births for the same population and year. [ICD-10: A34, O00-O95, O98-O99]

Formula:
(A/B) x 100 000
Numerator (A):
Number of maternal deaths (direct or indirect obstetric causes) in a given country, territory or geographical area in year z

Denominator (B):
Number of maternal deaths (direct or indirect obstetric causes) in a given country, territory or geographical area in year z

For the purpose of international reporting of maternal mortality, only those maternal deaths occurring before the end of the 42-day reference period should be included in the calculation of the various ratios and rates.
It is recommended to monitor late maternal deaths at the national level.

The maternal mortality ratio in the Americas is 52 maternal deaths per 100 000 live births. The maternal mortality ratio of country A is 350 per 100 000 live births. This means that in country A the risk of dying due to complications occurring during pregnancy, childbirth, or the postpartum period is almost seven times greater.

No disaggregation

Maternal mortality is difficult to measure and can be subject to significant underreporting. Obtaining reliable data is a challenge for many countries. Estimating maternal deaths requires a civil registry system with good coverage that records in- and out-of-hospital maternal deaths in a timely manner, and a good quality medical certificate indicating the cause of death. Otherwise, the accuracy of the estimates will be inadequate.

National health authority

Annual

United Nations (UN). Department of Economic and Social Affairs. Sustainable Development Goals (SDG).
Indicator 3.1.1: Maternal mortality ratio
SDG Target 3.1: By 2030, reduce the global maternal mortality ratio to less than 70 per 100 000 live births.
Available from: https://sdg.data.gov/

Pan American Health Organization. Strategic Plan of the Pan American Health Organization 2020-2025.
Indicator 6. Maternal mortality ratio (MMR) (deaths per 100,000 live births)
Available from: https://www.paho.org/en/documents/paho-strategic-plan-2020-2025

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from:
https://opendata.paho.org/en/core-indicators

ICD-10, International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Vol 2. Available from:
https://apps.who.int/iris/handle/10665/42980

Sociodemographic

Socioeconomic

The average number of years of schooling completed by the adult population age 25 or older in a given country, territory, or geographical area during a specific period, usually one year, excluding years spent repeating individual grades.

Years of study

Magnitude

Corrected

Mean years of schooling allows analysis of the impact of public policies aimed at strengthening education. As this indicator summarizes in a single number the educational level of the general population, it allows comparisons to be made between countries and within a country over time.

It allows evaluation of temporal and geographical trends in schooling between different populations and identification of at-risk groups in order to focus strategies to strengthen education. It is related to a country's educational system coverage and helps characterize its human capital. It is associated with a population's access to employment and income level.

As parents' educational level is directly related to the health status of their children, this is one of the indicators used to analyze child health and to plan strategies and interventions for health promotion, protection, and recovery.

The average number of years of schooling in the 25-year-old population comes from estimates made by the United Nations Educational, Scientific, and Cultural Organization (UNESCO), mainly using data from national population censuses and household/active population surveys. The definition of this indicator is in line with the revised recommendations on the International Standardization of Educational Statistics, adopted by UNESCO.

According to 2019 data, the average number of years of schooling of the 25-and-over population residing in country A is 8.5 years.

By sex

The indicator quantifies the population's educational attainment in a single number, which should not be interpreted as the average duration of education.

Because the World Bank obtains income data through household surveys, the accuracy of this indicator is affected by the timeliness, frequency, quality, and comparability of the surveys used.

United Nations Educational, Scientific, and Cultural Organization (UNESCO). Institute for Statistics. Available from:
http://uis.unesco.org/

Annual

Not applicable

UNESCO Education. Available from: https://www.unesco.org/en/education

Morbidity

Communicable diseases

Number of laboratory, clinically, or epidemiologically confirmed measles cases in a specific country, territory, or geographic area in a given year.

Cases

Magnitude

Crude

Measles is a highly contagious disease that can cause serious illness, lifelong complications, and death. It is caused by a virus in the paramyxovirus family and is usually transmitted through direct contact and by air (coughing and sneezing). The virus in the air or on infected surfaces remains active and contagious for up to two hours. An infected person can transmit the virus from four days before the rash appears to four days after. This virus can produce epidemics, especially in unvaccinated or malnourished children.

The number of measles cases quantifies the magnitude of this disease as a public health problem for a given population or geographic area. This indicator makes it possible to monitor the elimination of the disease, identify vulnerable populations, strengthen national surveillance systems, and enhance the identification of sick people to prevent further transmission through urgent vaccination of the population.

Monitoring this indicator tracks the progress of the Global Measles and Rubella Strategic Plan.

This indicator’s result is applicable to the design, implementation, and evaluation of health policies for the prevention and control of measles and the distribution of economic, human, and technological resources for this disease. Its applications include planning and evaluation of measles vaccination programs and prioritization of health care quality.

The data collected are mostly from national surveillance systems and are regularly reported to the Pan American Health Organization.

In country A, there were 11 cases of measles in 2019.

By sex

This indicator is affected by the performance and coverage of national measles surveillance systems, which in turn may be hampered by low early detection and underreporting of cases or untimely reporting.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core Indicators Portal. Available from:
https://opendata.paho.org/en/core-indicators
World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from:
https://www.who.int/data/gho/indicator-metadata-registry

World Health Organization (WHO). Measles; 2019. Available from: https://www.who.int
ews-room/fact-sheets/detail/measles

World Health Organization (WHO). Global Measles and Rubella Strategic Plan 2012–2020. Available from: http://apps.who.int/iris/bitstream/handle/10665/94384/9789241506236_eng.pdf?sequence=1

Sociodemographic

Demographic

The age dividing the population into two groups of equal size, meaning that there are as many people above the median age as people under the median.

Years

Index

Corrected/Predicted

This indicator highlights a population’s age distribution. It helps to assess demographic trends and changes, such as aging in a country or geographic area. It is used to develop and assess health and social security policies, among other purposes.

The value of this indicator comes from United Nations estimates, based on data representing estimated mid-year values, obtained by linear interpolation of the corresponding United Nations five-year medium-variant population projections.

The median age of a country in 2018 was 28.5 years. This means that, for that year, the estimated number of inhabitants under 28.5 years old was the same as those above that age.

In 2018, the median age in country A was 29 years. In country B, it was 35 years. This indicates that the latter country has an older population.

No disaggregation

The international comparability of this indicator may be limited by factors such as the quality of population censuses, demographic surveys, and national civil registration systems used to calculate estimates. One of these factors is the accuracy of age reporting.

The estimated value of this indicator may differ from country statistics due to factors such as methodological differences in developing population estimates and projections.

United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects. Available from:
https://population.un.org/wpp/

Annual

Not applicable

U. S. Census Bureau. International Programs, Glossary. Disponible en:
https://www.census.gov/programs-surveys/international-programs/about/glossary.html

United Nations, Department of Economic and Social Affairs, Statistics Division. Demographic and Social Statistics. Glossary of Demographic Terms. Available from:
https://population.un.org/wpp/GlossaryOfDemographicTerms/

United Nations, Department of Economic and Social Affairs, Statistics Division. Demographic and Social Statistics. Statistical Products and Databases. Available from:
https://unstats.un.org/unsd/demographic-social/products/

Haupt, A., Kane, T., Haub C. Population Reference Bureau’s Population Handbook (Sixth Edition) Washington, D.C. 2011. Available from:
https://www.prb.org/population-handbook/

Health service coverage

Human resources

Midwife density is defined as the total number of practising professional midwives, with formal education, in health facilities as of 31 December, per 10 000 population in a given country, territory or geographic area.

Professionals who plan, manage, provide and evaluate midwifery care and services before, during and after pregnancy and childbirth, both in the health services and in the community.
The International Standard Classification of Occupations code for this category is 2222 and 3222 (2008 revision). Physicians and nursing professionals are not included.

Per 10 000 population

Ratio

Crude

Professional childbirth care, as well as antenatal care, are key elements in reducing maternal and infant morbidity and mortality in a population. This indicator makes it possible to identify inequalities in the distribution of health resources and prioritize of human and economic resource allocation to specific populations. Its value is used to develop public policies to increase funding for maternal and child health, and to train, hire, and retrain skilled workers in this area.

The indicator also contributes to monitoring country progress in implementing the Plan of Action on Human Resources for Universal Access to Health and Universal Health Coverage 2018-2023 (https://iris.paho.org/handle/10665.2/49611?locale-attribute=pt) and the Global Strategy on Human Resources for Health 2030 (https://www.who.int/publications/i/item/9789241511131).

This indicator is calculated using as numerator the number of midwives reported by the countries of the Americas to the Pan American Health Organization (PAHO). This data is collected from secondary sources, such as health workers records or databases, aggregated data from health facilities (routine administrative records, health management information systems, censuses, and surveys from the district health information system), records of councils/chambers/professional associations, active population surveys, workforce surveys, national censuses, among other verifiable sources (official scientific articles, unpublished publications, central bank accounts).

Population figures from the United Nations Population Division are used for the denominator (https://population.un.org/wpp/)

According to 2019 data, the density of professional midwives in country A was 3.8 per 10 000 population. This means that, this country had 3.8 professional midwives per 10 000 population in 2019.

No disaggregation

The accuracy of this indicator depends on the coverage, recency, and quality of the data. In general, the public health sector tends to maintain more complete data on its workers. This may lead to underestimation of the active workforce in the private health, military, non-governmental organization, and religious sectors. Due to differences in data sources, there is considerable variability between countries in the coverage, regularity, quality, and integrity of the original data.

The value of this indicator may differ from figures calculated by each country due to differences, such as the populations used as denominator. Another factor to consider, depending on the nature of the original data source, is that the numerator could be limited to actively working professional midwives, or include all registered or licensed, even if their employment status is unknown.

It is important to consider that there are countries in the Region that do not have this professional.

National health authority

Annual

United Nations (UN). Department of Economic and Social Affairs. Sustainable Development Goals (SDG).
Indicator 3.c.1 Health worker density and distribution
Available from: https://sdgs.un.org/

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Pan American Health Organization (PAHO). Strategy on Human Resources for Universal Access to Health and Universal Health Coverage. Washington D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/34198

Pan American Health Organization (PAHO). Plan of Action on Human Resources for Universal Access to Health and Universal Health Coverage 2018-2023. Washington D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/49611?locale-attribute=pt

Pan American Health Organization (PAHO). Monitoring Framework for Universal Health in the Americas. Washington D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/53918

World Health Organization (WHO). 2018 Global Reference List of 100 Core Health Indicators (plus health-related SDGs). Geneva, 2018. Available from: https://apps.who.int/iris/bitstream/handle/10665/259951/WHO-HIS-IER-GPM-2018.1-eng.pdf

World Health Organization (WHO). National health workforce accounts: a handbook. Geneva, 2017. Available from: https://apps.who.int/iris/bitstream/handle/10665/259360/9789241513111-eng.pdf

International Labour Organization (ILO). International Standard Classification of Occupations 08 (ISCO-08). Available from: https://unstats.un.org/unsd/classifications/Family/Detail/1067

World Health Organization (WHO). Global Health Workforce statistics database. Available from: https://www.who.int/data/gho/data/themes/topics/health-workforce

International Confederation of Midwives (ICM). Available from: https://www.internationalmidwives.org/

Mortality

Environment

Deaths attributable to the joint effects of household and ambient air pollution on the population of a given country, territory, or geographic area, in a specific period of time, usually one year, after removing the confounding effect of a different age distribution of the population. Expressed per 100 000 population.

The causes of death considered in this indicator are acute respiratory infections in children under 5, cerebrovascular diseases, ischemic heart disease, chronic obstructive pulmonary disease, and lung cancer in the population aged 25 years or older.

Per 100 000 population

Rate

Corrected

Household and ambient air pollution is one of the main risk factors for illness and death, especially premature death. It is closely related to the epidemic of noncommunicable diseases and is responsible for the consumption of significant economic and human resources for health. This indicator reflects the risk in a certain population of dying due to household or ambient air pollution; therefore, it makes it possible to identify more vulnerable populations, where prevention strategies need to be focused.

This indicator is part of a group of indicators used at the international level that makes it possible to monitor countries’ progress in addressing the health risks of air pollution. Its value is applicable to strengthening the systems, structures, and processes needed to support monitoring and reporting on health trends associated with air pollution and its sources. This indicator is part of the Monitoring Framework for Universal Health in the Americas, to measure national progress in implementing policies aimed at strengthening health systems and achieving universal health.

This indicator’s value is applicable to multidisciplinary research on environmental pollution. It helps evaluate the effectiveness of strategies aimed at increasing equitable access to clean, safe energy sources.

This indicator’s value is from estimates by the World Health Organization (WHO)—the custodian for this and two other indicators related to air pollution and health. The estimation method involves using different data sources. Population data are from the United Nations Population Division (World Population Prospects). The proportion of households in a country relying primarily on polluting fuels and technologies for cooking is used as an indirect indicator for estimating the population’s exposure to household air pollution; these data are regularly collected in household surveys or population censuses and recorded in the WHO household energy database (https://www.who.int/data/gho/data/themes/air-pollution/who-household-energy-db). Data on exposure to ambient air pollution are from the WHO air quality database (https://www.who.int/data/gho/data/themes/air-pollution/who-air-quality-database). These data are then used as inputs in a statistical model to derive specific estimates for a particular country and year, which are then reported at the national, urban, and rural levels. The total number of deaths, years of life lost (YLL), years lived with disability (YLD) and disability-adjusted life years (DALYs) by country, sex, and age group for acute lower respiratory tract infections, chronic obstructive pulmonary disease, lung cancer, ischemic heart disease, and stroke are provided by WHO.

Estimates of mortality attributable to air pollution combine data on the increased (or relative) risk of a disease resulting from exposure, with information on the duration of the population’s exposure. These data are used to estimate the "population attributable fraction" (PAF), which is the fraction of disease in a given population that can be attributed to the exposure, in this case, both the annual mean concentration of particulate matter and exposure to solid fuels for cooking. Applying this fraction to the total disease burden yields the total number of deaths resulting from exposure to ambient and household air pollution.

Mortality attributed to ambient and household air pollution is estimated based on the calculation of attributable fractions of the combined population assuming independently distributed exposures and independent risks. PAF for ambient air pollution and PAF for home air pollution are evaluated separately.

More details on the methodology in:
World Health Organization (WHO). Burden of disease from household air pollution for 2016. Description of method. May 2018. Available from:
https://cdn.who.int/media/docs/default-source/air-quality-database/aqd-2018/hap_bod_methods_may2018.pdf?sfvrsn=d277d739_3
Ezzati M, Hoorn SV, Rodgers A, et al. Comparative Risk Assessment Collaborating Group. Estimates of global and regional potential health gains from reducing multiple major risk factors. Lancet. 2003; 362(9380):271–80. Available from:
https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(03)13968-2/fulltext

The mortality rate attributable to air pollution in country A in 2019 was 95.2 per 100 000 population. This means that, in that year, the population of country A had a risk of dying due to the joint effect of household and ambient air pollution of 95.2 per 100 000 population.

By sex

One of the limiting factors in estimating this indicator is that the parallel use of different fuels and technologies in households today is not fully captured in country data. This likely leads to an underestimation of exposure to household air pollution and also of its contribution to ambient pollution levels.

Due to the application of advanced statistical methods, this indicator’s estimated value may differ from each country’s calculations. These differences may be due to the use of different exposure data, exposure-risk estimates, and mortality data.

Since one of the necessary inputs for estimating the mortality rate attributable to air pollution is deaths, the accuracy of this indicator requires a civil registry system with complete coverage. Deaths must have medical certification of the cause of death and must be recorded in a timely manner in this system.

World Health Organization (WHO). The Global Health Observatory (GHO). Available from:
https://www.who.int/data/gho/indicator-metadata-registry

Annual

United Nations (UN). Department of Economic and Social Affairs. Sustainable Development Goals.
Indicator 3.9.1 Mortality rate attributed to household and ambient air pollution
Available from: https://sdgs.un.org/

Pan American Health Organization. Strategic Plan of the Pan American Health Organization 2020-2025.
Indicator 26. Mortality rate attributed to household and ambient air pollution
Available from: https://www.paho.org/en/documents/paho-strategic-plan-2020-2025

Pan American Health Organization (PAHO). Monitoring Framework for Universal Health in the Americas. Washington, D.C. 2021. Available from:
https://iris.paho.org/handle/10665.2/53918

World Health Organization (WHO). WHO indoor air quality guidelines: household fuel combustion. Geneva, 2021. Available from:
https://www.who.int/publications/i/item/9789241548885

World Health Organization (WHO). Burden of disease from the joint effects of household and ambient air pollution for 2016. Available from:
https://cdn.who.int/media/docs/default-source/air-quality-database/aqd-2018/ap_joint_effect_bod_results_may2018.pdf?sfvrsn=4dc44c26_3

World Health Organization (WHO). Road map for an enhanced global response to the adverse health effects of air pollution. World Health Assembly, 71. (‎2018)‎. Available from:
https://apps.who.int/iris/handle/10665/276321

Health system

Data quality

Number of deaths whose underlying causes were assigned garbage codes, expressed as a percentage of total deaths in a given country, territory, or geographical area, during a specific year.

Percentage

Proportion

Crude

The mortality garbage codes percentage is used to assess the quality of mortality information in detail. Quantifying the value of this indicator is essential to understand the quality and correct interpretation of causes of death and their effect on other mortality indicators.

Garbage codes refers to intermediate causes and terminal or unspecific complications that do not match the definition of underlying cause (an illness or injury that set off the chain of events directly leading to death, or the accident or violent act that produced the fatal injury). From a public health perspective, it is important to know the underlying cause in order to support prevention programs and design and implement effective policies and strategies.

Among the reasons for assigning these codes on the death certificate are: insufficient case information from the certifying physician; lack of training among personnel on how to correctly certify the death; and authorization given to non-medical personnel that often lack training and information on certification of underlying causes. Other reasons include failure to train and update mortality coders. This practice also inflates comorbidity at the time of death, complicating identification of the cause that set off the sequence of events leading to death. Garbage codes hide the true cause of death.

Generally speaking, cause-of-death statistics are essential when allocating resources to health services and planning and evaluating health policies. As a result, having correct and reliable underlying cause of death information is a public health priority.

Deaths with underlying causes appearing on the list of garbage codes are adapted from Naghavi et al. (2010) and the PAHO Regional Advisory Committee on Health Statistics (CRAES), 2012.

The percentage of garbage codes is calculated by the Pan American Health Organization (PAHO) from data reported by responsible national institutions.

Formula:
(A/B) x 100

Numerator (A):
Number of deaths assigned garbage codes in year z in a given country, territory, or geographic area.

Denominator (B):
Deaths from all causes in year z in a given country, territory, or geographic area.

PAHO garbage codes list (ICD-10):
A31.1, A40-A41, A48.0, A48.3, A49.9, A59, A60.0, A63.0, A71-A74, B00.0, B07, B08.1, B08.8, B30, B35-B36, B83.9, B94.8, B94.9, B99, C26, C39, C57.9, C63.9, C76, C80, D00-D13, D16-D18, D20-D24, D28-D48, D65, E85.3-E85.9, E86-E87, E88.9, F32-F33, F40-F42, F45-F48, F51-F53, F60-F98, G43-G45, G47-G52, G54, G56-G58, G80-G83, G91.1, G91.3-G91.8, G92, G93.1-G93.6, H00-H04, H05.2-H69, H71-H80, H83-H93, I10, I15, I26, I27.1, I44-I46, I49-I50, I51, I70, I74, I81, I99, J30, J33, J34.2, J35, J69, J80-J81, J86, J90, J93.8-J93.9, J94, J96, J98.1-J98.3, K00-K11, K14, K65-K66, K71-K72, (except K71.7), K75, K76.0-K76.4, K92.0-K92.2, L04-L08, L20-L25, L28-L87, L90-L92, L94, L98.0-L98.3, L98.5-L98.9, M03, M07, M09-M12, M14-M25, M35.3, M40, M43.6-M43.9, M45, M47-M60, M63-M71, M73-M79, M86, M95-M99, N14, N17-N19, N39.3, N40, N46,N60, N84-N93, N97, Q10-Q18, Q36, Q38.1, Q54, Q65-Q74, Q82-Q84, X59, Y10-Y34, Y86,Y87.2, Y89.

According to 2019 data, the percentage of deaths assigned garbage codes in country A was 11%; i.e., 11 out of every 100 deaths in country A that year were coded with garbage codes and therefore are not useful in public health analyses. The true underlying cause of death is unknown.

No disaggregation

The accuracy of this indicator is impacted by the coverage of civil registration systems, timely registration of deaths, and recorded information on causes of death. For example, when there is incomplete coverage in registration systems, the proportion of deaths assigned garbage codes will generally increase as coverage increases, even with no real drop in the quality of medical certification.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Naghavi, M., Makela, S., Foreman, K. et al. Algorithms for enhancing public health utility of national causes-of-death data. Population Health Metrics 8, 9 (2010). Available from: https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-8-9

Health system

Data quality

The difference between registered deaths and estimated deaths, expressed as a percentage of total estimated deaths in a given country, territory, or geographical area, in a given year.

Percentage

Proportion

Crude

This indicator measures the completeness of mortality data and is one of the indicators reflecting the performance of civil registration systems and vital statistics.

Generally speaking, complete, timely, and quality death statistics are essential for designing and evaluating targeted public policies to meet the needs of the population.

The indicator makes inequalities and barriers in access to registration systems visible and facilitates analysis of temporal and geographical trends. It helps to identify areas in need of improved civil registration systems and vital statistics coverage and implement and evaluate specific interventions to enhance deaths registration.

This indicator is calculated from the number of individual deaths registered in databases maintained by institutions responsible for vital statistics (e.g., the Ministry of Health or the National Institute of Statistics) and reported to the Pan American Health Organization (PAHO). These deaths are the numerator used when calculating the indicator.

For the denominator, population estimates and projections of the United Nations Population Division are used.

Formula:
(A/B) x 100

Numerator (A):
Number of registered deaths in a given country, territory or geographic area in year z.
Denominator (B):
Number of estimated deaths in a given country, territory or geographic area in year z.

Mortality under-registration in country A during 2019 was 10%; i.e., in this year, 10 out of every 100 deaths in country A were not registered.

No disaggregation

The value of this indicator may differ from that calculated by the country due to methodological differences affecting both the numerator and the denominator. These differences notably include extemporaneous records, that is, including in the numerator deaths that are registered in a specific year, regardless of the year of occurrence, instead of only those that occur in the reported year. Another difference lies in the death estimates used; for example, national versus international estimates.

There are countries in the Region that by law register deaths in the year of occurrence, while other countries register deaths in the year they are reported.

Numerator:
National health authority

Denominator:
Deaths estimated by international agencies

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

World Health Organization (WHO). Rapid assessment of national civil registration and vital statistics systems, WHO REFERENCE NUMBER: WHO/IER/HSI/STM/2010.1, 2010. Available from: https://www.who.int/publications/i/item/rapid-assessment-of-national-civil-registration-and-vital-statistics-systems

UNSTATS. Handbook on Civil Registration and Vital Statistics Systems: Management, Operation and Maintenance, Revision 1, NY, 2018. Available from: https://unstats.un.org/unsd/demographic-social/Standards-and-Methods/files/Handbooks/crvs/crvs-mgt-E.pdf

Health system

Health service

Percentage of municipalities in a given country, territory, or geographic area that in a specific year report coverage, in children under 1 year of age, equal to or greater than 95% for the third dose of diphtheria, tetanus, and pertussis vaccine (DTP3).

Municipalities are defined as the third administrative level of a country, with the country level being the first, unless otherwise indicated.

Percentage

Proportion

Crude

Immunization is one of the most cost-effective public health interventions and is essential to reducing infant mortality. DTP3 vaccine coverage is a measure of the performance of the health system in administering childhood vaccination. This indicator identifies gaps in immunization program coverage at the subnational level that may remain hidden when national analysis is performed. Its value enables more efficient allocation of economic, human, and technological resources.

Spatial analysis of immunization program coverage is a critical tool for obtaining new information and making informed decisions. Spatial analysis is used when obtaining estimates, detecting patterns and variations in time, and interpreting observed changes.

Annually, countries officially report coverage figures through the PAHO/WHO/UNICEF Joint Notification Form. The data comes from their administrative information systems. Using these figures, PAHO calculates regional coverage according to the weighted average of the United Nations population.

According to 2019 data, 80% of the municipalities in country A reported ≥ 95% DTP3 coverage.

No disaggregation

The value of this indicator depends on the performance of technical programs and their ability to capture data at the subnational level. Ideally, countries would also have a well-functioning national immunization registry that allows information to be disaggregated at the municipal level. The methodology used to determine immunization coverage may differ from country to country.

National health authority

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Pan American Health Organization (PAHO). Monitoring Framework for Universal Health in the Americas. Washington, D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/53918

Pan American Health Organization (PAHO). Immunization data and statistics. Available from: https://www.paho.org/en/topics/immunization/immunization-data-and-statistics

Mortality

Child health

The quotient between the number of children born alive in a given country, territory, or geographic area that died before the age of 28 days in a specific calendar year and the total number of live births for the same population and year, as reported by the corresponding health authority. Expressed per 1 000 live births.

Live birth means the complete expulsion or extraction from its mother of a product of conception, irrespective of the duration of pregnancy, that, after such expulsion or extraction, breathes or shows any other evidence of life, such as beating of the heart, pulsation of the umbilical cord, or definite movement of voluntary muscles, whether or not the umbilical cord has been cut or the placenta is attached. Each product of such childbirth that meets these conditions is considered a live birth.

1 000 live births

Rate

Crude/Corrected

This indicator quantifies the scope of neonatal mortality and highlights it as a public health problem for a given population or geographic area.

The estimated neonatal mortality rate reflects a population’s health status and social, economic, and environmental conditions. It makes it possible to identify health inequities and populations with specific risk factors and is related to maternal and child health care access, quality, and timeliness.

This indicator is applicable to the design, implementation, and evaluation of health policies and the distribution of economic, human, and technological resources aimed at improving maternal and child health, particularly prenatal and neonatal care. Its result helps strengthen professional care for childbirth, breastfeeding, and the Expanded Program on Immunization.

It allows for analysis of the geographic and time trend of neonatal mortality in a given population.

The neonatal mortality rate uses the number of children born alive who died before the age of 28 days as the numerator and the total number of live births as the denominator.

Formula:
(A/B) x 1 000 live births

Numerator (A):
Number of children born alive who died before the age of 28 days in a given country, territory and geographic area during year z

Denominator (B):
Total number of live births in the same population during year z

To estimate the indicator by sex, the following formula is applied:
(A/B) x 1 000 live births

Numerator (A):
Number of children born alive of a given sex, who died before the age of 28 days, in a specific country, territory, or geographic area during year z

Denominator (B):
Total number of live births in the same population during year z

Country A’s neonatal mortality rate for 2019 was 26.3 per 1 000 live births; that is, in that year 26 children born alive died before the age of 28 days per 1 000 live births.

By sex

The neonatal mortality rate requires a civil registry system with good coverage, and births and deaths must be recorded in a timely manner in this system; otherwise, this indicator will not be sufficiently accurate.

The value of this indicator may differ from each country’s value due to methodological differences such as the application of methods to correct underreporting of births and deaths.

National health authority

Annual

United Nations (UN). Department of Economic and Social Affairs. Sustainable Development Goals (SDG).
Indicator 3.2.2 Neonatal mortality rate.
Available from: https://sdgs.un.org/goals

Pan American Health Organization. Strategic Plan of the Pan American Health Organization 2020-2025.
Indicator 3. Neonatal mortality rate
Available from: https://www.paho.org/en/documents/paho-strategic-plan-2020-2025

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho

ICD-10, International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Vol 2. Available from: https://icd.who.int/browse10/Content/statichtml/ICD10Volume2_en_2010.pdf

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Morbidity

Communicable diseases

The number new cases of people diagnosed with human immunodeficiency virus (HIV), in a given country, territory, or geographical area, during a specific period.

100 000 population

Rate

Crude

Human immunodeficiency virus (HIV) is an infection that attacks the body's immune system. Those affected have a high susceptibility to other diseases, such as tuberculosis and some types of cancer. HIV is a preventable disease, and despite having no cure, antiretroviral therapy (ART) reduces viral replication, shrinking the load to an undetectable level. ART prevents mother-to-child transmission of HIV during pregnancy, childbirth, and lactation. Those receiving ART and who have suppressed the virus will not transmit it to their sexual partners.

The indicator is used to monitor the epidemic’s trends and dynamics within a country or territory and assess access to diagnosis.

This indicator is one of the inputs applied when estimating the HIV burden. It contributes to public health policy-making, planning and allocation of economic, human, and technological resources to respond to the disease. This metric, disaggregated by sex and age, identifies populations in need of direct preventive and surveillance strategies, communication campaigns, and access to diagnosis and early antiretroviral treatment to reduce impact on the immune system and transmission. It is also considered when implementing counseling and accompaniment programs for patients with HIV.

The number of HIV cases is obtained from each country's HIV surveillance and control system. This information is reported annually to the Pan American Health Organization, where the rate is calculated based on data from the total population indicator.

In 2019, the rate of new HIV diagnoses in country A was 25.2 per 100 000 people, i.e., there were 25.2 reported new cases of people diagnosed with HIV per 100 000 people in country A.

By sex

The value of the new HIV diagnoses rate is impacted by the coverage, effectiveness, and quality of surveillance and control systems. One factor to consider when interpreting this indicator is that the diagnosis year may differ from the year the person acquired HIV. Another issue affecting the indicator's accuracy is timely access to laboratory diagnostic tests.

National health authority

Annual

Pan American Health Organization. Strategic Plan of the Pan American Health Organization 2020-2025.
Indicator: 16. Incidence rate of HIV infections
Available from: https://www.paho.org/en/documents/paho-strategic-plan-2020-2025

World Health Organization (WHO). The Global Health Observatory (GHO). Available from: https://www.who.int/data/gho/indicator-metadata-registry

Joint United Nations Programme on HIV/AIDS (UNAIDS). UNAIDS Data 2017. Available from: https://www.unaids.org/en

World Health Organization (WHO). Consolidated strategic information guidelines for HIV in the health sector. Geneva, 2015. Available from: http://apps.who.int/iris/bitstream/handle/10665/164716/9789241508759_eng.pdf

World Health Organization (WHO). HIV/AIDS. Available from: https://www.who.int/health-topics/hiv-aids#tab=tab_1

Morbidity

Communicable diseases

The woman-to-man ratio of new diagnoses of human immunodeficiency virus (HIV) in a given country, territory, or geographical area, during a specific period.

Male:female

Ratio

Crude

Human immunodeficiency virus (HIV) is an infection that attacks the body's immune system. Those affected have a high susceptibility to other diseases, such as tuberculosis and some types of cancer. HIV is a preventable disease, and despite having no cure, antiretroviral therapy (ART) reduces viral replication, shrinking the load to an undetectable level. ART prevents mother-to-child transmission of HIV during pregnancy, childbirth, and lactation. Those receiving ART and who have suppressed the virus will not transmit HIV to their sexual partners.

The indicator is applied to monitor the differences between men and women in the trends and dynamics of the epidemic within a country or territory. Its value reflects the differentiated results of infection prevention and control strategies by sex.

This indicator is one of the inputs to estimate the HIV burden. It contributes to public health policy-making with a gender approach and for planning and allocation of economic, human, and technological resources to respond to the disease. This metric, disaggregated by sex and age, identifies populations in need of direct preventive and surveillance strategies, communication campaigns, and access to diagnosis and early antiretroviral treatment to reduce impact on the immune system and transmission. The indicator contributes to implementing counseling and accompaniment programs for patients with HIV.

The number of new HIV diagnoses is obtained from data reported to the Pan American Health Organization (PAHO) by national authorities, compiled mostly from national HIV surveillance and control systems.
The sex ratio is calculated by PAHO.

In 2019, the sex ratio of new HIV diagnoses in country A was 2.0. This means for every new HIV diagnosis in a woman, there were two in men. In other words, twice as many new HIV diagnoses were reported in men than in women.

No disaggregation

The value of the new HIV diagnoses rate is impacted by the coverage, effectiveness, and quality of surveillance and control systems. One factor to consider when interpreting this indicator is that the diagnosis year may differ from the year the person acquired HIV. Another issue affecting the indicator's accuracy is timely access to laboratory diagnostic tests.

National health authority

Annual

Not applicable

World Health Organization (WHO). The Global Health Observatory (GHO). Available from:
https://www.who.int/data/gho/indicator-metadata-registry

World Health Organization (WHO). Consolidated strategic information guidelines for HIV in the health sector. Geneva, 2015. Available from: http://apps.who.int/iris/bitstream/handle/10665/164716/9789241508759_eng.pdf

Joint United Nations Programme on HIV/AIDS (UNAIDS). UNAIDS Data 2017. Available from: https://www.unaids.org/en

World Health Organization (WHO). HIV/AIDS. Available from: https://www.who.int/health-topics/hiv-aids#tab=tab_1

Mortality

Cause of death

The estimated total number of deaths from noncommunicable diseases in the population, in a given country, territory or geographic area during a specific calendar year, divided by the total number of this population, generally estimated in the middle of the same year (1 July), after removing the effect of differences in the age distribution of the population. Expressed per 100 000 population.

Per 100 000 population

Rate

Corrected

This indicator reflects a population’s lifestyles, socio-economic development, and health status and is also related to population aging and rapid, poorly planned urbanization. Its analysis makes it possible to identify populations with greater risk factors for dying from noncommunicable diseases and to encourage research in this area.

Its result is applicable to the design, implementation, and evaluation of health policies on noncommunicable diseases and the distribution of economic, human, and technological resources for the prevention, diagnosis, treatment, and control of this group of pathologies, among others. Its applications include, for example, evaluating over time the effectiveness of interventions promoting healthy lifestyles and socio-economic measures to reduce health inequities and increase timely access to care.

Removing the effect of differences in the age distribution by using a standard population makes it possible to analyze the time trend and geographic distribution of deaths from noncommunicable diseases, in the same population or across populations.

The numerator of this indicator uses deaths from noncommunicable diseases, from the World Health Organization (WHO) Global Health Estimates (GHE). These estimates are based on data from multiple sources, such as national civil registry systems, estimates from WHO technical programs, the United Nations and inter-agency groups, and the Global Burden of Disease, among others.

The underlying causes of death correspond to codes C00 - C97, D00 - D48, D55 - D64 (except D64.9), D65 - D89, E03 - E07, E10 - E34, E65 - E88, F01 - F99, G06 - G98 (except G14), H00 - H61, H68 - H93, I00 - I99, J30 - J98, K00 - K92, L00 - L98, M00 - M99, N00 - N64, N75 - N98, Q00 - Q99, X41 - X42, X44 - X45, R95 of the International Classification of Diseases, Tenth Revision (ICD-10).

The populations used in the denominator of the noncommunicable diseases mortality rate are from estimates by the United Nations Population Division.

Applying advanced statistical models, and depending on the data source used and its quality, adjustments are made to avoid bias and ensure compliance with standards and comparability of results across countries. If the data are from civil registry systems, adjustments include, but are not limited to, underreporting of deaths, unknown age and sex, and ill-defined causes of death, as well as garbage codes.

For more details on methodology, see:
World Health Organization (WHO). Division of Data, Analytics and Delivery for Impact (DDI). WHO methods and data sources for country-level causes of death 2000-2019. December 2020. Available from: https://www.who.int/docs/default-source/gho-documents/global-health-estimates/ghe2019_cod_methods

The noncommunicable diseases mortality rate is adjusted for age by direct standardization, applying estimated age-specific mortality rates, for both sexes or for a given sex, to the World Health Organization (WHO) World Standard Population.

The age-adjusted noncommunicable diseases mortality rate for 2019 was 93 per 100 000 population in country A and 60 per 100 000 population in country B; that is, in 2019 noncommunicable diseases were responsible for the death of 93 people per 100 000 population of country A, compared to country B, where 60 people died from the same group of causes per 100 000 population. This means that, after removing the effect of differences in the age distributions in the two countries, the risk of dying from noncommunicable diseases in 2019 was higher in the population of country A than in country B.

By sex

The age-adjusted noncommunicable diseases mortality rate is a fictitious value, the main purpose of which is to allow for the comparison of this indicator across populations or in the same population over time; therefore, it should be interpreted with caution.

The estimated value of the age-adjusted noncommunicable diseases mortality rate will depend on the standard population used for its adjustment; therefore it may differ from each country’s estimates. Other methodological considerations that influence its result are the use of a different group of ICD-10 codes and the application of algorithms to correct underreporting and redistribute ill-defined causes, among others.

Estimating the noncommunicable diseases mortality rate requires a civil registry system with good coverage. Death from this group of pathologies must be recorded in a timely manner in this system, and certification of the cause of death must be of good quality; otherwise, the estimates will not be sufficiently accurate.

World Health Organization (WHO). Global Health Estimates. Available from: https://www.who.int/data/global-health-estimates

Annual

Not applicable

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Ahmad O., Boschi-Pinto C., Lopez A., Murray C., Lozano R., Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No. 31 EIP/GPE/EBD World Health Organization 2001. Available from: https://www.researchgate.net/publication/284696312_Age_Standardization_of_Rates_A_New_WHO_Standard

World Health Organization (WHO). World Health Data Platform. The Global Health Observatory. Indicators. Available from: https://www.who.int/data/gho/indicator-metadata-registry

Health service coverage

Human resources

Nursing associates professionals’ density is defined as the number of practising nursing professionals, with formal education, in health facilities as of 31 December in a specific year, per 10 000 population in a given country, territory or geographic area.

Nursing associates professionals provide basic nursing care and health advice, monitor health status of users, and carry out pre-established care and treatment plans under supervision.

The definitions of the International Standard Classification of Occupations (ISCO-08) are adapted to the context of the Region of the Americas and its countries.

Per 10 000 population

Ratio

Crude

Nursing associates professionals are an integral part of the health care system. This indicator makes it possible to identify inequalities in the distribution of health resources and prioritize human and economic resource allocation to specific populations. Its value is used for the formulation of public policies that allow promoting health financing, as well as the professionalization of this group of workers, recruitment and retention.

This indicator also contributes to monitoring country progress in implementing the Plan of Action on Human Resources for Universal Access to Health and Universal Health Coverage 2018-2023 (https://iris.paho.org/handle/10665.2/49611?locale-attribute=pt) and the Global Strategy on Human Resources for Health 2030 (https://www.who.int/publications/i/item/9789241511131).

This indicator is calculated using as numerator the number of nursing associates professionals reported by the countries of the Americas to the Pan American Health Organization (PAHO).
This data is collected from secondary sources, such as health workers records or databases, aggregated data from health facilities (routine administrative records, health management information systems, censuses, and surveys from the district health information system), records of councils/chambers/professional associations, active population surveys, workforce surveys, national censuses, among other verifiable sources (official scientific articles, unpublished publications, central bank accounts).

Population figures from the United Nations Population Division are used for the denominator (https://population.un.org/wpp/).

According to 2019 data, the density of nursing associates professionals in country A was 19.3 per 10 000 population. This means that, in all health facilities, in 2019 this country had 19.3 nursing associates professionals per 10 000 population.

No disaggregation

The accuracy of this indicator depends on the coverage, recency, and quality of the data. In general, the public health sector tends to maintain more complete data on its workers. This may lead to underestimation of the active workforce in the private health, military, non-governmental organization, and religious sectors. Due to differences in data sources, there is considerable variability between countries in the coverage, regularity, quality, and integrity of the original data.

The value of this indicator may differ from figures calculated by each country due to differences, such as the populations used as denominator. Another factor to consider, depending on the nature of the original data source, is that the numerator could be limited to actively working nursing associate professionals, or include all registered or licensed, even if their employment status is unknown.

National health authority

Annual

United Nations (UN). Department of Economic and Social Affairs. Sustainable Development Goals (SDG).
Indicator 3.c.1 Health worker density and distribution
Available from: https://sdgs.un.org/

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Pan American Health Organization (PAHO). Strategy on Human Resources for Universal Access to Health and Universal Health Coverage. Washington D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/34198

Pan American Health Organization (PAHO). Plan of Action on Human Resources for Universal Access to Health and Universal Health Coverage 2018-2023. Washington D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/49611?locale-attribute=pt

Pan American Health Organization (PAHO). Monitoring Framework for Universal Health in the Americas. Washington D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/53918

World Health Organization (WHO). 2018 Global Reference List of 100 Core Health Indicators (plus health-related SDGs). Geneva, 2018. Available from: https://apps.who.int/iris/bitstream/handle/10665/259951/WHO-HIS-IER-GPM-2018.1-eng.pdf

World Health Organization (WHO). National health workforce accounts: a handbook. Geneva, 2017. Available from: https://apps.who.int/iris/bitstream/handle/10665/259360/9789241513111-eng.pdf

International Labour Organization (ILO). International Standard Classification of Occupations 08 (ISCO-08). Available from: https://unstats.un.org/unsd/classifications/Family/Detail/1067

World Health Organization (WHO). Global Health Workforce statistics database. Available from: https://www.who.int/data/gho/data/themes/topics/health-workforce

Health service coverage

Human resources

Nursing professionals’ density is defined as the number of practising nursing professionals, with high formal education, in health facilities as of 31 December in a specific year, per 10 000 population in a given country, territory or geographic area.

Professionals who provide prevention, promotion, treatment and rehabilitation services to people who need health care. They are responsible for planning and managing the care of users, including supervision of other health workers. They work autonomously or in a team, both in the field of health services and in the community. Includes: Professional Nurse, Registered Nurse, Specialist Nurse, Advanced Practice Nurse, Clinical Nurse, Public Health Nurse, Nursing Technician, Nursing Technologist.

The definitions of the International Standard Classification of Occupations (ISCO-08) are adapted to the context of the Region of the Americas and its countries.

Per 10 000 population

Ratio

Crude

Nursing professionals are an integral part of the health care system. This indicator makes it possible to identify inequalities in the distribution of health resources and prioritize human and economic resource allocation to specific populations. Its value is used to develop public policies to increase funding for health, and to train, hire, and retrain skilled workers in this area.

The indicator also contributes to monitoring country progress in implementing the Plan of Action on Human Resources for Universal Access to Health and Universal Health Coverage 2018-2023 (https://iris.paho.org/handle/10665.2/49611?locale-attribute=pt) and the Global Strategy on Human Resources for Health 2030 (https://www.who.int/publications/i/item/9789241511131).

This indicator is calculated using as numerator the number of nursing professionals reported by the countries of the Americas to the Pan American Health Organization (PAHO). This data is collected from secondary sources, such as: health workers records or databases, aggregated data from health facilities (routine administrative records, health management information systems, censuses, and surveys from the district health information system), records of councils/chambers/professional associations, active population surveys, workforce surveys, national censuses, among other verifiable sources (official scientific articles, unpublished publications, central bank accounts).

Population figures from the United Nations Population Division are used for the denominator (https://population.un.org/wpp/).

According to 2019 data, the density of nursing professionals in country A was 19.3 per 10 000 population. This means that, in all health facilities, this country had 19.3 nurses per 10 000 population in 2019.

No disaggregation

The accuracy of this indicator depends on the coverage, recency, and quality of the data. In general, the public health sector tends to maintain more complete data on its workers. This may lead to underestimation of the active workforce in the private health, military, non-governmental organization, and religious sectors. Due to differences in data sources, there is considerable variability between countries in the coverage, regularity, quality, and integrity of the original data.

The value of this indicator may differ from figures calculated by each country due to differences, such as the populations used as denominator. Another factor to consider, depending on the nature of the original data source, is that the numerator could be limited to actively working nursing professionals, or include all registered or licensed, even if their employment status is unknown.

National health authority

Annual

United Nations (UN). Department of Economic and Social Affairs. Sustainable Development Goals (SDG).
Indicator 3.c.1 Health worker density and distribution
Available from: https://sdgs.un.org/

Pan American Health Organization (PAHO)/World Health Organization (WHO). Core indicators Portal. Available from: https://opendata.paho.org/en/core-indicators

Pan American Health Organization (PAHO). Strategy on Human Resources for Universal Access to Health and Universal Health Coverage. Washington D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/34198

Pan American Health Organization (PAHO). Plan of Action on Human Resources for Universal Access to Health and Universal Health Coverage 2018-2023. Washington D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/49611?locale-attribute=pt

Pan American Health Organization (PAHO). Monitoring Framework for Universal Health in the Americas. Washington D.C., 2021. Available from: https://iris.paho.org/handle/10665.2/53918

World Health Organization (WHO). 2018 Global Reference List of 100 Core Health Indicators (plus health-related SDGs). Geneva, 2018. Available from: https://apps.who.int/iris/bitstream/handle/10665/259951/WHO-HIS-IER-GPM-2018.1-eng.pdf

World Health Organization (WHO). National health workforce accounts: a handbook. Geneva, 2017. Available from: https://apps.who.int/iris/bitstream/handle/10665/259360/9789241513111-eng.pdf

International Labour Organization (ILO). International Standard Classification of Occupations 08 (ISCO-08). Available from: https://unstats.un.org/unsd/classifications/Family/Detail/1067

World Health Organization (WHO). Global Health Workforce statistics database. Available from: https://www.who.int/data/gho/data/themes/topics/health-workforce

International Council of Nurses (ICN). Available from: https://www.icn.ch/