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COVID-19 Projections: IHME is producing and regularly updating projections for total and daily deaths, daily infections and testing, hospital resource use, and social distancing due to COVID-19 for a number of countries. Access current projections.

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Annual estimates were produced for child growth failure (CGF) among children younger than 5 years of age at the 5x5 km-level for 105 low- and middle-income countries (LMICs) between 2000 and 2019. These estimates were produced using geo-positioned data from 460 household surveys, including the Demographic and Health Survey (DHS), Multiple Indicator Cluster Survey (MICS), and other country‐specific surveys. Countries and subnational units outside of these 105 LMICs were supplemented with GBD results.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates for 105 LMICs
  • CSV files of aggregated estimates for 195 countries at the national level, 105 LMICs plus GBD subnational locations at the admin 1 level, and 105 LMICs at the admin 2 level
  • Code files used to generate the estimates

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Annual estimates were produced for the prevalence and incidence of malaria and malaria mortality across all ages for all countries between 2000 and 2019. These estimates were produced using geo-positioned data from household surveys and routine surveillance data. Survey sources include the Demographic and Health Survey (DHS), Malaria Indicator Survey (MIS) and other country-specific surveys.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates of malaria prevalence, incidence, and mortality
  • CSV files of aggregated malaria prevalence, Incidence, and mortality for each country at zero, first and second administrative divisions

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Annual estimates were produced for the prevalence and incidence of diarrhea and diarrhea-related mortality among children younger than 5 years of age at the 5x5 km-level for 94 low- and middle-income countries (LMICs) between 2000-2019. These estimates were produced using geo-positioned data from 466 household surveys, including the Demographic and Health Survey (DHS), Multiple Indicator Cluster Survey (MICS), and other country‐specific surveys. Countries and subnational units outside of these 94 LMICs were supplemented with GBD results.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates for 94 LMICs
  • CSV files of aggregated estimates for 195 countries at the national level, 94 LMICs plus GBD subnational locations at the admin 1 level, and 94 LMICs at the admin 2 level
  • Code files used to generate the estimates

Get Data Files

Annual estimates were produced for overweight prevalence for children under 5 years of age at the 5x5 km-level for 105 low- and middle-income countries (LMICs) between 2000 and 2019. These estimates were produced using a geo-positioned dataset created from 420 household surveys. Countries and subnational units outside of these 105 LMICs were supplemented with GBD results.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates of under-5 overweight prevalence for 105 LMICs
  • CSV files of aggregated for 195 countries at the national level, 105 LMICs plus GBD subnational locations at the first-level administrative divisions, and 105 LMICs at the second level administrative divisions
  • Code files used to generate the estimates

Get Data Files

Estimates from the Global Burden of Disease Study 2019 (GBD 2019) were used to create an index which estimates global progress towards universal health coverage (UHC) and specifically UHC effective coverage in 204 countries and territories in 1990, 2010, and 2019. The UHC effective coverage index is comprised of 23 indicators drawn across a range of health service areas and is meant to represent healthcare needs over the life course. This dataset contains estimates for the UHC effective coverage index, each UHC effective coverage indicator, and indicator-specific weights by location-year. Code used to produce the estimates is also available for download.
 
Results were published in The Lancet in September 2020 in “Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019”.

Estimates were produced for lymphatic filariasis (LF) all-age prevalence at the 5x5 km-level in endemic countries across Africa, Asia, and Hispaniola, annually between 2000 and 2018. Bayesian time series estimates were produced for 17 small area geographies in South America, the Indian Ocean, and Oceania. These estimates were produced using data on LF and geographical locations from endemicity mapping surveys, sentinel surveillance surveys, transmission assessment surveys (TAS), and other sources.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates of LF prevalence rate, counts, and posterior probability that prevalence was lower than 2% in 2018
  • CSV files of aggregated estimates of LF prevalence rate, count and posterior probability of prevalence below 2% (2018) for each country at the zero, first, and second administrative divisions
  • Code files used to generate the estimates

Annual estimates were produced for access to drinking water and sanitation Facilities at the 5x5 km-level for 90 low- and middle-income countries (LMICs) for 2000-2017. These estimates were produced using a geo-positioned dataset created from 634 household surveys. Survey sources used include the Demographic and Health Survey (DHS) and UNICEF Multiple Indicator Cluster Survey (MICS) series, and other country‐specific surveys.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates of drinking water and sanitation facility coverage percent (percent of people with the given type of access) and number (number of people with the given type of access)
  • CSV files of aggregated estimates for each country at zero, first and second administrative divisions
  • Code files used to generate the estimates

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Annual estimates were produced for oral rehydration therapy (ORT) coverage for children under 5 years of age who had diarrhea at the 5x5 km-level for 94 low- and middle-income countries (LMICs) between 2000-2017. These estimates were produced using a geo-positioned dataset created from 385 household surveys. Survey sources used include the Demographic and Health Survey (DHS) and UNICEF Multiple Indicator Cluster Survey (MICS) series, and other country‐specific surveys.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates of oral rehydration therapy percent (percent of children with diarrhea who received treatment) and number (number of children with diarrhea who received treatment)
  • CSV files of aggregated oral rehydration therapy coverage percent and number for each country at zero, first and second administrative divisions
  • Code files used to generate the estimates

IHME researchers forecasted population from 2018 to 2100 for 195 countries and territories. They produced these using estimates from the Global Burden of Disease Study (GBD) 2017 and and forecasts for fertility, migration, and mortality rates. This dataset includes the following: past estimates for population and deaths; forecasts for population, deaths, life expectancy, live births, total fertility rate (TFR), and migration; and annual life tables for 2018-2100. The projections for population, deaths, life expectancy, live births, total fertility rate (TFR) each include a reference scenario as well as four alternative scenarios that reflect faster or slower trajectories for two key drivers of fertility rates: education of females and access to modern reproductive health services, measured using contraceptive met need.

Click here to access the life tables.

Annual estimates were produced for adult male circumcision (MC) prevalence and the number of circumcised and uncircumcised males ages 15-49 at the 5x5 km-level for 38 countries in sub-Saharan Africa between 2000 and 2017. These estimates were produced using a geo-positioned dataset created from 109 household surveys. Survey sources used include the Demographic and Health Survey (DHS), AIDS Indicator Survey (AIS), Multiple Indicator Cluster Survey (MICS), Core Welfare Indicators Questionnaire Survey (CWIQ), Population-based HIV Impact Assessment Survey (PHIA), and other country‐specific surveys.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates of male circumcision (MC) prevalence and the number of circumcised and uncircumcised males ages 15-49
  • CSV files of aggregated circumcision estimates for each country at zero, first and second administrative divisions
  • Code files used to generate the estimates

Annual estimates were produced for the prevalence and incidence of diarrhea and diarrhea-related mortality among children younger than 5 years of age at the 5x5 km-level for 94 low- and middle-income countries (LMICs) between 2000-2017. These estimates were produced using geo-positioned data from 466 household surveys. Survey sources used include the Demographic and Health Survey (DHS) and UNICEF Multiple Indicator Cluster Survey (MICS) series, and other country‐specific surveys.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates of under-5 diarrhea prevalence, incidence, and diarrhea-related mortality
  • CSV files of aggregated under-5 diarrhea prevalence, incidence, and diarrhea-related mortality for each country at zero, first and second administrative divisions
  • Code files used to generate the estimates

Get Data Files

Research by the Global Burden of Disease Health Financing Collaborator Network estimated tuberculosis spending for 134 low- and middle-income countries for 2000-2017. The estimates cover tuberculosis spending disaggregated by source into three domestic financing source categories (government, out-of-pocket, and prepaid private) and development assistance for health (DAH). Spending is also disaggregated by function, including care and treatment, prevention, and other spending. Domestic tuberculosis spending by source and function was estimated based on data from sources including the WHO Global Tuberculosis database, the Global Fund, WHO National Health Accounts and sub-accounts, WHO Global Health Expenditure database (GHED), National Tuberculosis Reports, and Ministry of Health Reports. Development assistance for tuberculosis data were drawn from IHME's 2019 Development Assistance for Health Database. Estimates are reported in constant 2019 United States dollars.

Research by the by the Global Burden of Disease Health Financing Collaborator Network estimated estimated malaria spending for 106 countries for 2000-2017. The estimates cover malaria spending disaggregated by source into three domestic financing source categories (government, out-of-pocket, and prepaid private) and development assistance for health (DAH). Domestic malaria spending estimates were produced from a diverse set of data, including the World Malaria Report, WHO National Health Accounts and sub-accounts, the Global Fund Price Quality Reporting, WHO Global Price Reporting Mechanism, Management Sciences for Health reference prices, the Malaria Atlas Project, and more. Development assistance for malaria data were drawn from IHME's 2019 Development Assistance for Health Database. This database is also informed by a diverse set of sources, including program reports, budget data, national estimates, and NHAs. Estimates are reported in constant 2019 United States dollars.

Research by the Global Burden of Disease Health Financing Collaborator Network estimated HIV/AIDS spending for 134 low- and middle-income countries for 2000-2017. The estimates cover HIV/AIDS spending disaggregated by source into three domestic financing source categories (government, out-of-pocket, and prepaid private) and development assistance for health (DAH). Spending is also disaggregated by function, including care and treatment, prevention, and other spending. Domestic HIV/AIDS spending by source and function was estimated based on data from sources including National AIDS Spending Assessments (NASA), the Global Fund, WHO National Health Accounts and sub-accounts, UNAIDS Global AIDS Response Progress Reports (GARPR), the GARPR database, UNAIDS health financing dashboard, and the AIDS data hub. Development assistance for HIV/AIDS data were drawn from IHME's 2019 Development Assistance for Health Database. Estimates are reported in constant 2019 United States dollars.

Research by the Global Burden of Disease Health Financing Collaborator Network produced retrospective health spending estimates for 1995-2017 for 195 countries and territories. The estimates cover total health spending, health spending disaggregated by source into three domestic financing source categories (government, out-of-pocket, and prepaid private), and development assistance for health (DAH). Domestic health spending source data came primarily from the WHO’s Global Health Expenditure Database (GHED). DAH data came from a diverse set of sources, including program reports, budget data, national estimates, and National Health Accounts (NHAs). The resulting estimates were used to help produce prospective health spending estimates for 2018-2050. Estimates are reported in constant 2019 United States dollars, constant 2019 purchasing-power parity-adjusted (PPP) dollars, and as a percent of gross domestic product.

Research by the Global Burden of Disease Health Financing Collaborator Network produced projected health spending estimates for 2018-2050 for 195 countries and territories. The estimates cover total health spending, health spending disaggregated by source into three domestic financing source categories (government, out-of-pocket, and prepaid private), and development assistance for health (DAH). Retrospective health spending estimates for 1995-2017 and key covariates (including GDP per capita, total government spending, total fertility rate, and fraction of the population older than 65 years) were used to forecast GDP and health spending through 2050. Estimates are reported in constant 2019 US dollars, constant 2019 purchasing-power parity-adjusted (PPP) dollars, and as a percent of gross domestic product.

This version of the Development Assistance for Health (DAH) Database includes estimates for 1990-2019, which are based on project databases, financial statements, annual reports, IRS 990s, and correspondence with agencies. The DAH Database enables comprehensive analysis of trends in international disbursements of grants and loans for health projects in low- and middle-income countries from key agencies. The data are disaggregated by source of funds, channel of funding, country and geographic region, health focus areas, and program areas. New in 2019: The current estimates of DAH incorporated improvements in methodology such as leveraging additional project-level descriptions from the Creditor Reporting System for the allocation of disbursements channeled through non-governmental organizations (NGOs) and ongoing refinement of the project’s keyword search list.

To better understand the data and how to use it, please refer to the IHME DAH Database 2019 User Guide.

Annual estimates were produced for overweight and wasting prevalence for children under 5 years of age at the 5x5 km-level for 105 low- and middle-income countries (LMICs) between 2000-2017. These estimates were produced using a geo-positioned dataset created from 420 household surveys. Survey sources used include the Demographic and Health Survey (DHS) and UNICEF Multiple Indicator Cluster Survey (MICS) series, and other country‐specific surveys.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates of under-5 overweight and wasting prevalence
  • CSV files of aggregated overweight and wasting prevalence for each country at zero, first, and second administrative divisions
  • Code files used to generate the estimates

Get Data Files

IHME researchers produced this dataset as part of an analysis measuring and forecasting progress by countries towards education-related Sustainable Development Goal (SDG) targets. Annual estimates were created for the average years of schooling and single-year distribution of educational attainment by sex for adults ages 25-29 for 1970 to 2018. Projections were also generated for these indicators to 2030. Estimates were created for the 195 countries and territories examined in the Global Burden of Disease 2017 study. The estimates were produced using a compiled database of 3,180 nationally representative surveys and censuses describing the distribution of years of schooling by age and sex.

IHME has produced forecasts which show hospital bed use, need for intensive care beds, and ventilator use due to COVID-19 based on projected deaths for countries in the European Economic Area (EEA). Forecasts at the subnational level are included for three of these: Germany, Italy, and Spain. These projections are produced by models based on observed death rates from COVID-19, and include uncertainty intervals. They incorporate information about social distancing and other protective measures and are being updated daily with new data. These forecasts were developed in order to provide hospitals, policy makers, and the public with crucial information about how expected need aligns with existing resources, so that cities and states can best prepare.

Access current projections

IHME has produced forecasts which show hospital bed use, need for intensive care beds, and ventilator use due to COVID-19 based on projected deaths for all 50 U.S. states. These projections are produced by models based on observed death rates from COVID-19, and include uncertainty intervals. They incorporate information about social distancing and other protective measures and are being updated daily with new data. These forecasts were developed in order to provide hospitals, policy makers, and the public with crucial information about how expected need aligns with existing resources, so that cities and states can best prepare.

Access current projections

The HeartRescue Global Project, a multi-country, multi-year effort aims to improve access and quality for acute cardiovascular disease (CVD), including ST-elevation myocardial infarction (STEMI) and sudden cardiac arrest (SCA) in selected locations in China, India, and Brazil. This dataset is the product of a HeartRescue program impact evaluation. It includes results of a baseline health facility and emergency medical service (EMS) survey conducted in Beijing and Shanghai, China. Data were collected from three secondary hospitals and one tertiary hospital. Data were collected about facility capacity, equipment availability, pharmaceutical and supply stocks, staffing, and services provided. The data were collected through computer-assisted personal interviews (CAPI).

The HeartRescue Global Project, a multi-country, multi-year effort aims to improve access and quality for acute cardiovascular disease (CVD), including ST-elevation myocardial infarction (STEMI) and sudden cardiac arrest (SCA) in selected locations in China, India, and Brazil. This dataset is the product of a HeartRescue program impact evaluation. It includes results of a baseline household survey conducted in Beijing and Shanghai, China. Data were collected from 1,500 individuals ages 18 or older in each city, for a total of 3,000 respondents. Information was collected from respondents through computer-assisted personal interviews (CAPI). Data were collected about demographics, health history and status, health behaviors, health care use, and knowledge, attitudes and practices regarding CVD, risk factors, and CVD care.

The HeartRescue Global Project, a multi-country, multi-year effort aims to improve access and quality for acute cardiovascular disease (CVD), including ST-elevation myocardial infarction (STEMI) and sudden cardiac arrest (SCA) in selected locations in China, India, and Brazil. This dataset is the product of a HeartRescue program impact evaluation. It includes results of a baseline household survey conducted in Bangalore, India. Data were collected from 2,400 households. One eligible adult per household was randomly selected from the household roster. Information was collected from respondents through computer-assisted personal interviews (CAPI). Data were collected about demographics, health history and status, health behaviors, health care use, and knowledge, attitudes and practices regarding CVD, risk factors, and CVD care.

The HeartRescue Global Project, a multi-country, multi-year effort aims to improve access and quality for acute cardiovascular disease (CVD), including ST-elevation myocardial infarction (STEMI) and sudden cardiac arrest (SCA) in selected locations in China, India, and Brazil. This dataset is the product of a HeartRescue program impact evaluation. It includes results of a baseline health facility emergency medical service (EMS) survey conducted in Bangalore, India. Data were collected from 8 EMS units. Data were collected about facility capacity, equipment availability, pharmaceutical and supply stocks, staffing, and services provided. The data were collected through computer-assisted personal interviews (CAPI).

The HeartRescue Global Project, a multi-country, multi-year effort aims to improve access and quality for acute cardiovascular disease (CVD), including ST-elevation myocardial infarction (STEMI) and sudden cardiac arrest (SCA) in selected locations in China, India, and Brazil. This dataset is the product of a HeartRescue program impact evaluation. It includes results of a baseline health facility and emergency medical services (EMS) survey conducted in Vitória da Conquista, Brazil. Data were collected from three private hospitals, one public hospital, and one EMS unit. Data were collected about facility capacity, equipment availability, pharmaceutical and supply stocks, staffing, and services provided. The data were collected through computer-assisted personal interviews (CAPI).

The HeartRescue Global Project, a multi-country, multi-year effort aims to improve access and quality for acute cardiovascular disease (CVD), including ST-elevation myocardial infarction (STEMI) and sudden cardiac arrest (SCA) in selected locations in China, India, and Brazil. This dataset is the product of a HeartRescue program impact evaluation. It includes results of a baseline household survey conducted in Vitória da Conquista, Brazil. An adult age 30 years or older was interviewed from each eligible household. Topics covered in the interview included demographic and household characteristics; healthcare use and access; health knowledge, attitudes, and practices related to CVD health; CVD risk factors; and participants' health histories. In total, data were collected from 1,054 households.

The Disease Expenditure Project (DEX) at IHME produced estimates for US spending on health care according to 3 types of payers (public insurance [including Medicare, Medicaid, and other government programs], private insurance, or out-of-pocket payments) and by health condition, age group, sex, and type of care for 1996 through 2016. Types of care include ambulatory care, inpatient care, nursing care facility stay, emergency department care, dental care, prescribed pharmaceutical care, and government administration and net cost of insurance programs. Government budgets, insurance claims, facility records, household surveys, and official US records from 1996 through 2016 were used to produce the results. Spending estimates were produced for 154 conditons, which were aggregated into 14 health categories. This dataset contains estimates for the aggregate health categories.

These data are the product of a collaboration between the Institute for Health Metrics and Evaluation (IHME) and the Universidad Autónoma de Yucatán (UADY): a cross-sectional study exploring the delays faced during the search for care by caregivers of children under the age of 5 who died in the State of Yucatán, Mexico, during 2015–2016. Two datasets resulting from the project are available for download. The first contains results of a household census in which interviews were conducted with caregivers of the deceased children. The interview consisted of two parts, a standardized verbal autopsy using neonatal and child modules of the Population Health Metrics Research Consortium (PHMRC) Shortened Questionnaire and a section with questions about health care-seeking behavior during the final illness and household characteristics. The second dataset includes the review of medical records for children who died in medical units of the Secretary of Health of Yucatán.

HealthRise is a collaborative multicountry initiative to implement and evaluate innovative community-based programs intended to improve heart disease and diabetes care in underserved communities. Conducted as part of HealthRise Brazil, this household survey was carried out in approximately 2,000 households in Padre Paraíso in the state of Minas Gerais and Poções in the state of Bahia. Data were collected regarding sociodemographic background, risk factors, medical history, and knowledge, attitudes, and practices related to NCDs. Anthropometric data, including height, weight, and abdominal circumference were also collected, in addition to blood pressure and random blood glucose (RBG) measurements. The data were collected through computer-assisted personal interviews (CAPI) with one adult age 30 years or older in each household.

HealthRise is a collaborative multicountry initiative to implement and evaluate innovative community-based programs intended to improve heart disease and diabetes care in underserved communities. Conducted as part of HealthRise India, this health facility survey was carried out in 48 facilities in the Shimla district in the state of Himachal Pradesh and the Udaipur district in the state of Rajasthan. Data were collected about facility capacity, equipment availability, pharmaceutical and supply stocks, staffing, and services provided. The data were collected through computer-assisted personal interviews (CAPI).

Annual estimates were produced for child growth failure (CGF), expressed as stunting, wasting, and underweight prevalence for children under 5 years of age, at the 5x5 km-level for 105 low- and middle-income countries (LMICs) between 2000-2017. These estimates were produced using a geo-positioned dataset created from 460 household surveys. Survey sources used include the Demographic and Health Survey (DHS) and UNICEF Multiple Indicator Cluster Survey (MICS) series, and other country‐specific surveys.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates of under-5 stunting, wasting, and underweight prevalence
  • CSV files of aggregated stunting, wasting and underweight prevalence for each country at zero, first and second administrative divisions
  • Code files used to generate the estimates

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This dataset contains estimates produced for educational attainment for adults ages 15-49, and the 20–24 subgroup, by sex at the 5x5 km-level for 105 low- and middle-income countries for 2000-2017. It provides years of education and proportion of the population attaining key levels of education. These estimates were produced using individual records from 528 geo-referenced household sample survey and census sources.

The dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates of mean educational attainment, and proportion of the population achieving zero, less than primary, primary, and secondary schooling for adults ages 15-49 and 20-24, divided by sex
  • CSV files of aggregated estimates for each country at the zero, first, and second administrative divisions
  • Code files used to generate the estimates

Get Data Files

HealthRise is a collaborative multicountry initiative to implement and evaluate innovative community-based programs intended to improve heart disease and diabetes care in underserved communities. Conducted as part of HealthRise South Africa, this health facility survey was carried out in 38 facilities in the Pixley ka Seme district in the province of Northern Cape and the uMgungundlovu district in the province of KwaZulu-Natal. The survey was adapted from questionnaires created and conducted for the HealthRise projects in South Africa and India in 2015. Data were collected about facility capacity, equipment availability, pharmaceutical and supply stocks, staffing, and services provided. Patient exit interviews were also conducted with eligible patients at health facilities. The data were collected through computer-assisted personal interviews (CAPI).    

HealthRise is a collaborative multicountry initiative to implement and evaluate innovative community-based programs intended to improve heart disease and diabetes care in underserved communities. Conducted as part of HealthRise India, this health facility survey was carried out in 30 facilities in Shimla district in the state of Himachal Pradesh. The survey was adapted from a questionnaire created and conducted for the HealthRise project in India in 2015. Data were collected about facility capacity, equipment availability, pharmaceutical and supply stocks, staffing, and services provided. Patient exit interviews were also conducted with eligible patients at health facilities. The data were collected through computer-assisted personal interviews (CAPI).

Annual estimates were produced for mortality probability and death counts in three age groups – neonates (0-28 days old), infants (under-1 year old), and under-5 (0-5 years old) – at the 5x5 km-level in 99 low- and middle-income countries (LMICs) between 2000-2017. These estimates were produced using data on child mortality and geographical locations from censuses and several household survey series. Survey sources used include the Demographic and Health Survey (DHS) and UNICEF Multiple Indicator Cluster Survey (MICS) series, and other country‐specific surveys.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates of mortality probability and death counts in 3 age bins
  • CSV files of aggregated mortality probability and death count estimates for each country at the zero, first, and second administrative divisions, by age group
  • Code files used to generate the estimates

Estimates were produced for lower respiratory infection (LRI) incidence, prevalence, and mortality among children under 5 at the 5x5 km-level in 52 countries in Africa between 2000-2017. These estimates were produced using data extracted from 191 household surveys that had questions about the prevalence of cough with difficulty breathing among children under 5, and allowed for subnational geolocation. The surveys include the Demographic and Health Survey (DHS), Multiple Indicator Cluster Survey (MICS), World Bank, and other country‐specific surveys. Collectively, they provided 56,628 total data points, corresponding to 53,592 survey clusters and 3,036 subnational polygon boundaries.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates of LRI incidence, prevalence, and mortality
  • CSV files of aggregated estimates for each country at the zero, first, and second administrative divisions
  • Code files used to generate the estimates

Country profiles were created for 43 sub-Saharan African countries highlighting travel times to the most accessible health facility from areas with Viral Hemorrhagic Fever (VHF) spillover event potential, travel times to the nearest at-risk location for VHFs, and an assessment of how travel times would change given new infrastructure in a country.

This dataset includes the following:

  • Four PDF files per country
    • Country-specific estimates of the travel times described above
    • Maps of the analysis stratified by facility type
    • Maps depicting the uncertainty around the modeled VHF spillover event potential estimates using differing thresholds
    • Table of travel times to the nearest at-risk location for any VHF from all hospitals in a country, shaded by hours of travel time
  • Code files used to generate the estimates

Get Data Files

Estimates were produced for exclusive breastfeeding (EBF) prevalence among infants under 6 months of age at the 5x5 km-level in 49 countries in Africa between 2000-2017. These estimates were produced using data extracted from 188 household surveys that had complete records of questions relating to infant feeding and geographical information. The surveys include the Demographic and Health Survey (DHS), Multiple Indicator Cluster Survey (MICS), and country‐specific and other multinational surveys.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates of EBF prevalence
  • CSV files of aggregated estimates for each country at the zero, first, and second administrative divisions
  • Code files used to generate the estimates

This dataset contains 882 unique occurrences of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) extracted from 217 reports published between October 2012 and February 2018. Occurrences of MERS-CoV among humans, mammals, and environmental sources were extracted and geopositioned to the highest resolution possible (up to 5x5km). Special attention was given to spillover events (i.e., humans becoming infected from mammals). Thus, MERS-CoV occurrences meeting the criteria for index or unspecified cases are assigned their own rows; alternatively, multiple mammal, import, or secondary cases are collapsed to one row in the dataset.

IHME researchers participated in study that applied statistical mapping techniques to the most extensive database of dengue case locations to date to predict global environmental suitability for the virus as of 2015. The database was created with published literature, case reports, and informal online sources, with usable location information extracted from each source. The final occurrence database contains 13,604 unique occurrences, which represent a unique location where one or more dengue cases occurred within one year.

The database includes the following:

  • A dengue occurrence point dataset, which contains precise point locations where dengue has occurrence in the past
  • A dengue occurrence polygon dataset, which contains small administrative units within which dengue has occurred in the past
  • Other disease background points, which contains point locations where other non-dengue infectious diseases have occurred in the past

IHME researchers conducted a systematic review of published literature containing data on onchocerciasis-related infection and disability indicators from 1975-2017, encompassing the period of implementation for control and local elimination programs among the Americas, Africa and Yemen. Ultimately, geographic data, as well as relevant epidemiological metadata, were extracted from 259 peer-reviewed sources reporting prevalence of onchocerciasis. This dataset contains the following: a screening sheet detailing all studies reviewed; a database of onchocerciasis prevalence containing 14,043 unique location, diagnostic, age and sex-specific records marked for collapse where a single geo-position is shared between multiple records; and a conversion file that connects the names of diagnostics extracted and standardized during the review to diagnostic codes and diagnostic groups.

Estimates were produced for HIV prevalence among adults ages 15-49 and the corresponding number of people living with HIV (PLHIV) at the 5x5 km-level in 47 countries in Africa between 2000-2017. These estimates were produced using data on HIV and geographical locations from seroprevalence surveys and sentinel surveillance of antenatal care clinics.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates of HIV prevalence, PLHIV, and eight covariates constructed for the analysis: prevalence of male circumcision, self-reported STI symptoms, marriage or living with a partner as married, one’s current partner living elsewhere, condom use at last sexual encounter, reported intercourse among young adults, and multiple partners in the last year for men and for women
  • CSV files of aggregated HIV prevalence and PLHIV estimates for each country at the zero, first, and second administrative divisions
  • Code files used to generate the estimates

Research by the Global Burden of Disease Health Financing Collaborator Network estimated HIV/AIDS spending for 137 low- and middle-income countries for 2000-2016. The estimates cover HIV/AIDS spending disaggregated by source into three domestic financing source categories (government, out-of-pocket, and prepaid private) and development assistance for health (DAH). Spending is also disaggregated by function, including care and treatment, prevention, and other spending. Domestic HIV/AIDS spending by source and function was estimated based on five major data sources: the AIDSinfo online database, Global Fund concept notes and proposals, National Health Accounts (NHAs), National AIDS Spending Assessments, and the AIDS data hub. Development assistance for HIV/AIDS data were drawn from IHME's 2018 Development Assistance for Health Database. Estimates are reported in constant 2018 United States dollars.

Research by the Global Burden of Disease Health Financing Collaborator Network produced projected health spending estimates for 2017-2050 for 195 countries and territories. The estimates cover total health spending, and health spending disaggregated by source into three domestic financing source categories (government, out-of-pocket, and prepaid private) and development assistance for health (DAH). Retrospective health spending estimates for 1995-2016 and key covariates (including GDP per capita, total government spending, total fertility rate, and fraction of the population older than 65 years) were used to forecast GDP and health spending through 2050. Estimates are reported in constant 2018 US dollars, constant 2018 purchasing-power parity-adjusted (PPP) dollars, and as a percent of gross domestic product.

Research by the Global Burden of Disease Health Financing Collaborator Network produced retrospective health spending estimates for 1995-2016 for 195 countries and territories. The estimates cover total health spending, and health spending disaggregated by source into three domestic financing source categories (government, out-of-pocket, and prepaid private) and development assistance for health (DAH). Domestic health spending source data came primarily from the WHO’s Global Health Expenditure Database (GHED). DAH data came from a diverse set of sources, including program reports, budget data, national estimates, and National Health Accounts (NHAs). The resulting estimates were used to help produce prospective health spending estimates for 2017-2050. Estimates are reported in constant 2018 United States dollars, constant 2018 purchasing-power parity-adjusted (PPP) dollars, and as a percent of gross domestic product.

This version of the Development Assistance for Health (DAH) Database includes estimates for 1990-2018, which are based on project databases, financial statements, annual reports, IRS 990s, and correspondence with agencies. The DAH Database enables comprehensive analysis of trends in international disbursements of grants and loans for health projects in low- and middle-income countries from key agencies. The data are disaggregated by source of funds, channel of funding, country and geographic region, health focus areas, and program areas. New in 2018: the addition of China as a source of funding; the inclusion of the Coalition for Epidemic Preparedness Innovations and European Economic Area as channels of disbursements; and the addition of drug resistance/antimicrobial resistance (AMR) as a program area.

To understand the framework used to track DAH, users of the database should review IHME's Financing Global Health 2018 report and methods annex.

Research by the IHME estimated malaria spending for 106 countries which were malaria-endemic over 2000-2016 or became malaria-free after 2000. The estimates cover malaria spending disaggregated by source into three domestic financing source categories (government, out-of-pocket, and prepaid private) and development assistance for health (DAH). Domestic malaria spending estimates were produced from a diverse set of data, including National Malaria Control Programs, the WHO’s World Malaria Reports (WMRs), country spending estimates reported to the Global Fund, and National Health Accounts (NHAs). Development assistance for malaria data were drawn from IHME's 2018 Development Assistance for Health Database. This database is also informed by a diverse set of sources, including program reports, budget data, national estimates, and NHAs. Estimates are reported in constant 2018 United States dollars.

Estimates were produced for diphtheria-pertussis-tetanus (DPT) vaccine coverage and dropout for children ages 12-23 months at the 5x5 km-level in 52 countries in Africa between 2000-2016. These estimates were produced using data from 183 population-based household surveys conducted in Africa between 2000 and 2016 that included dose-specific information on DPT coverage (from vaccine cards or maternal recall in the absence of vaccine cards) and subnational geographical location for children ages 12-59 months.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates of DPT1 coverage (the proportion of children who received one or more doses of DPT), DPT3 coverage (three or more doses), and relative and absolute DPT1-3 dropout
  • CSV files of aggregated estimates for each country at the first and second administrative divisions
  • Code files used to generate the estimates

The Salud Mesoamérica Initiative (SMI) focuses on reducing inequalities in maternal and child health in Mesoamerica. This dataset is the product of an SMI impact evaluation. It includes results of a follow-up health facility survey conducted in two provincial-level regions in Panama: Emberá-Wounaan and Guna Yala. In total, 39 facilities were surveyed. These represent facilities that provide ambulatory-, basic-, and complete-level Essential Obstetric and Neonatal Care (EONC) services. Surveyors collected data through interviews with facility personnel and direct observation. They recorded information on general facility characteristics, infrastructure, staff, supplies, equipment, and the availability of key maternal and child health care services. They also performed medical record reviews, extracting data on record-keeping, family planning, treatment practices related to uncomplicated births and medical complications experienced by mothers or infants during delivery, and child medical services.

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