IHME Data

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. 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

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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”.

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

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

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 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 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.

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

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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.

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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 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 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 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.

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.

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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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).    

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

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

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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 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.

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 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.

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.