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The Premise Education COVID-19 Health Services Disruption Survey 2021 is a follow-up series to the COVID-19 Health Services Disruption Survey 2020 series conducted in July 2020. These surveys were developed to assess the level of disruption to a range of health services resulting from the COVID-19 pandemic and subsequent government mandates and changes in behavior to mitigate the spread of the disease. Data generated from this survey is not intended to be used as an overall estimate of the level of health service delivery.

This survey was conducted in 51 countries using the smartphone-based Premise data collection platform. Respondents were 23,376 individual members of the general population who served as caregiver to school-age children. The survey focused on the level of disruption to education for school-age children.

The Premise Child Health COVID-19 Health Services Disruption Survey 2021 is a follow-up series to the COVID-19 Health Services Disruption Survey 2020 series conducted in July 2020. These surveys were developed to assess the level of disruption to a range of health services resulting from the COVID-19 pandemic and subsequent government mandates and changes in behavior to mitigate the spread of the disease. Data generated from this survey is not intended to be used as an overall estimate of the level of health service delivery.

This survey was conducted in 51 countries using the smartphone-based Premise data collection platform. Respondents were 7,383 individual members of the general population who served as caregiver to at least one child under the age of two years old. The survey focused on the level of disruption to vaccination and general health services for children under the age of two.

This dataset includes estimates of total health care spending in the US for 6 race/ethnicity groups by 6 types of care, sex, 19 age groups, and 7 health condition, as well as an aggregate of all health conditions, for the years 2002-2016. To produce these estimates, data on self-reported race and Hispanic ethnicity, age, sex, insurance coverage, knowledge of having key health conditions, and information about health system encounters (visits, admission, or prescriptions), diagnoses, and healthcare spending were extracted from the Medical Expenditure Panel Survey (2002-2016), the National Health Interview Survey (2002; 2016), and the Medicare Current Beneficiary Survey (2002-2012). These data were combined with healthcare spending estimates form the Disease Expenditure Project (1996-2016). Estimates are reported in inflation-adjusted 2016 US dollars.

This dataset includes estimates of primary health care (PHC) expenditures, PHC expenditures in ambulatory settings, and PHC expenditures disaggregated by the System of Health Accounts (SHA) health care function category in low- and middle-income countries (LMICs) from 2000 through 2017. Three data sources were used to estimate PHC expenditures: recently published health expenditure estimates for each LMIC, which were constructed using 1662 country-reported National Health Accounts (NHAs); proprietary data from IQVIA to estimate expenditure of prescribed pharmaceuticals for PHC; and household surveys and costing estimates to estimate inpatient vaginal delivery expenditures.

This dataset includes collected country-reported health expenditures and national health expenditure estimates for 195 countries from 2000 through 2017 by the System of Health Accounts (SHA) healthcare function (HC) and healthcare provider (HP) categories. The estimates are saved in level space, per capita, and as a share of total health spending. The estimates were created using 1662 country-years and 110,070 data points of health expenditures extracted and compiled from existing National Health Accounts (NHA).

Estimates were produced for environmental suitability of onchocerciasis presence at the 5x5 km-level in endemic countries across Africa. These estimates were produced using a boosted regression tree (BRT) analysis trained on reported onchocerciasis presence data from endemicity mapping surveys, surveillance during elimination programs, and other sources. The model was trained using data from 1974–2015; final estimates were produced using covariate values for 2013.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates of environmental suitability for onchocerciasis presence.
  • Code files used to generate the estimates.

This dataset provides estimates of the impact of COVID-19 on routine childhood immunizations (DTP3 and MCV1) monthly in 2020 by country, Global Burden of Disease (GBD) super-region, and globally. Indicators include mean and 95% uncertainty intervals for the estimated relative disruption attributable to COVID-19, estimated coverage, and expected coverage in the absence of COVID-19 for all locations and estimated doses missed, expected doses missed in the absence of COVID-19, and estimated doses missed attributable to COVID-19 for global and GBD super-region locations. These estimates were produced using administrative data and reports from electronic immunization systems, with mobility data as a model input.

Estimates of vaccination coverage for 11 childhood vaccines (first-dose bacillus Calmette-Guérin [BCG], first- and third-dose diphtheria-tetanus-pertussis [DTP1, DTP3], third-dose hepatitis B [HepB3], third-dose Haemophilus influenzae type b [Hib3], first- and second-dose measles [MCV1, MCV2], third-dose pneumococcal conjugate vaccine [PCV3], third-dose polio [Pol3], first-dose rubella-containing vaccine [RCV1], and complete rotavirus [RotaC, two or three doses]) were produced for 204 countries and territories between 1980 and 2019 as part of the Global Burden of Disease Study 2020, Release 1 (GBD 2020 R1). The estimation process primarily utilized household survey microdata, household survey report data in the absence of microdata, and estimates of country-reported coverage data.

This dataset includes the following:

  • CSV files for national-level estimates of vaccine coverage, by vaccine
  • Code files used to generate the estimates

Annual estimates were produced for exclusive breastfeeding prevalence among infants under 6 months of age at the 5x5 km-level for 94 low- and middle-income countries (LMICs) between 2000 and 2019. These estimates were produced using a geo-positioned dataset created from 394 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 of exclusive breastfeeding prevalence among infants under 6 months of age for 94 LMICs
  • CSV files of aggregated for 195 countries at the national level, 94 LMICs plus GBD subnational locations at the first-level administrative divisions, and 94 LMICs at the second-level administrative divisions
  • Code files used to generate the estimates

Get Data Files

Annual estimates were produced for HIV incidence and mortality among adults ages 15-49 at the 5x5 km-level for 44 countries in sub-Saharan Africa between 2000 and 2018. These estimates were produced using a geo-positioned dataset created from 717 sources representing antiretroviral treatment data in UNAIDS Spectrum country files, country-level reports from the Health Management Systems database, and PEPFAR data; HIV seroprevalence surveys; ANC Sentinel Surveillance data; covariate surveys; and country specific surveys.

This dataset includes the following:

  • CSV files of aggregated incidence and mortality estimates for each country at zero, first and second administrative divisions
  • Code files used to generate the estimates

Estimates of smoking prevalence among young people ages 15 to 24 and age of smoking initiation were produced by sex and year for 204 countries and territories for 1990-2019. Files available in this record include estimates of the prevalence of smoking among young people, mean age of initiation, and quantiles from the distribution of initiation age. Study results were published in The Lancet Public Health in May 2021 in "Spatial, temporal, and demographic patterns in smoking prevalence and initiation among young people in 204 countries and territories, 1990-2019."

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

Estimates of chewing tobacco use and the burden attributable to this risk factor were produced by sex, age group, and year for 204 countries and territories for 1990-2019. The files in this record include estimates of chewing tobacco use prevalence for people ages 15 and older by sex, age group, and year. Estimates of disease burden attributable to chewing tobacco use are available in the GBD Results Tool.

For additional GBD results and resources, visit the GBD 2019 Data Resources page.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

Estimates of smoking tobacco use and the burden attributable to this risk factor were produced by sex, age group, and year for 204 countries and territories for 1990-2019. Files available in this record include estimates of the prevalence of smoking tobacco use, number of people that currently use smoked tobacco products, and supply-side tobacco availability and consumption. Estimates of disease burden attributable to smoking tobacco use are available through the GBD Results Tool.

For additional GBD results and resources, visit the GBD 2019 Data Resources page.

Established in 2015 by the United Nations, the Sustainable Development Goals (SDGs) specify 17 universal goals for achieving "peace and prosperity" by reducing inequality, improving health and education, and more. Each goal contains a number of specific targets and indicators for measurement and is intended to be achieved by 2030. This dataset provides estimates on progress for indicator 5.2.1, the proportion of age-standardized prevalence of ever-partnered women ages 15 years and older who experienced physical or sexual violence by a current or former intimate partner in the last 12 months. Progress on this indicator is reported as index values (scaled 0 to 100) which cover 204 countries and territories from 1990 to 2019. The indicator is a component of SDG 5 (Achieve gender equality and empower all women and girls), target 5.2 (Eliminate all forms of violence against all women and girls in the public and private spheres, including trafficking and sexual and other types of exploitation).

These data are the product of a collaboration between the Institute for Health Metrics and Evaluation (IHME) and the Universidad Autónoma de Yucatán (UADY). The objective of the project was to improve maternal and child health and the quality of health information in the state of Yucatán, Mexico through assessing the knowledge of alarm signs, and access and utilization of health services, among caregivers of children under 5 years of age. The population under study includes caregivers of children under 5 in 8 municipalities in Yucatán. This survey covered topics related to the identification of symptoms for common causes of death, health-care seeking behaviors, and a short series of questions related to COVID-19. In total, responses were collected from 500 respondents.

These data are the product of a collaboration between the Institute for Health Metrics and Evaluation (IHME) and the Universidad Autónoma de Yucatán (UADY). The objective of the project was to improve maternal and child health and the quality of health information in the state of Yucatán, Mexico through assessing the knowledge of alarm signs, and access and utilization of health services, among caregivers of children under 5 years of age. This dataset includes the results of a household census and caregiver interviewer. The population under study includes caregivers of children under 5 in 8 municipalities in Yucatán. In total, data were collected from 2,996 households.

This dataset contains predicted 2017 smoking prevalence levels under unrealized tobacco control policy scenarios: 1) If WHO-attributed country achievement scores for select components of its MPOWER policy package (smoke-free (P), health warnings (W), and advertising (E)), and cigarette’s affordability (RIP) remained at the level they were at in 2008; 2) If the price of a cigarette pack was I$7.73 or higher; 3) If all countries had implemented each of the P, W, and E policies at the highest level; and 4) If countries had implemented both higher cigarette prices and P, W, and E policies at the highest level. Results were produced by sex and age group globally and for 155 countries. The dataset also includes data used to produce the counterfactual analysis, including GBD 2017 smoking prevalence estimates, different tobacco control policy indicators, cigarette prices and affordability, and more.

Annual estimates were produced for the HIV mortality rate and number of deaths due to HIV by sex and age group in the 0-80+ year range at the municipality level in six countries in Latin America: Brazil, Mexico, Guatemala, Costa Rica, Colombia, and Ecuador. The estimates cover from 2000 to 2017 in Brazil, Colombia, and Mexico; from 2009 to 2017 in Guatemala; from 2004 to 2014 in Ecuador; and from 2014 to 2016 in Costa Rica. Input data sources consisted of vital registration (VR) mortality data — anonymized individual-level records from all deaths reported in each country’s VR system occurring between the years of study.

This dataset includes the following:

  • CSV files of estimates of the HIV mortality rate and the number of HIV deaths by age group and sex for each country at zero, first, and second administrative divisions
  • Code files used to generate the estimates
  • The shapefile used to inform the estimates

Annual estimates were produced for oral rehydration therapy coverage for children under 5 years of age who had diarrhea at the second administrative-level unit in Senegal, Mali, and Sierra Leone between 2000–2018. These estimates were produced using a geo-positioned dataset created from 23 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:

  • CSV files of aggregated oral rehydration therapy coverage estimates at the second administrative level. Estimates are provided for three measures: Any oral rehydration solutions, Recommended home fluids only, and No oral rehydration therapy
  • Code files used to generate the estimates

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

This dataset provides annual estimates for 1950–2019 for numbers of deaths, mortality rate, and probability of death by sex for 6 age groups under 5 years: 0–6 days (early neonatal), 7–27 days (late neonatal), 1–5 months, 6–11 months, 12–23 months, and 2–4 years. There were 7417 sources used to produce these estimates. These included 28,016 location-years of vital registration data, 481 surveys with complete birth histories, and 1081 sources on summary birth histories.

For additional GBD results and resources, visit the GBD 2019 Data Resources page.

Estimates were produced for first-dose coverage of measles-containing vaccine (MCV1) at the 5x5 km-level in 101 low- and middle-income countries (LMICs) between 2000-2019. These estimates were produced using data on vaccination coverage and geographical locations from 354 household-based surveys.

This dataset includes the following:

  • GeoTIFF raster files for pixel-level estimates of MCV1 coverage
  • CSV files of aggregated MCV1 coverage estimates for each country at the first and second administrative unit divisions
  • Code files used to generate the estimates

Get Data Files (CSV data and documentation are also available in the "Files" tab above.) 

The COVID-19 Health Services Disruption Survey 2020 is a series of surveys developed to assess the level of disruption to a range of health services resulting from the COVID-19 pandemic and subsequent government mandates and changes in behavior to mitigate the spread of the disease.

This survey was conducted by ORB International via telephone interview using nationally representative samples in Kenya, Nigeria, and South Africa. Respondents were individual members of the general population. Data were collected from 3,058 respondents. The survey focused on the level of disruption to the provision of general and reproductive health services, including access to medication and family planning.

The survey was developed specifically to assess the change in levels of service delivery prior to, and immediately following, the onset of the COVID-19 global pandemic. Data generated from this survey is not intended to be used as an overall estimate of the level of health service delivery.

The COVID-19 Health Services Disruption Survey 2020 is a series of surveys developed to assess the level of disruption to a range of health services resulting from the COVID-19 global pandemic and subsequent government mandates and changes in behavior to mitigate the spread of the disease.

This survey was conducted in 76 countries using the smartphone-based Premise data collection platform. Respondents were individual members of the general population in 20 African countries where malaria is endemic. Data were collected from 14,615 respondents. The survey focused on the level of disruption to malaria prevention activities and malaria testing and treatment.

The survey was developed specifically to assess the change in levels of service delivery prior to, and immediately following, the onset of the COVID-19 global pandemic. Data generated from this survey is not intended to be used as an overall estimate of the level of health service delivery.

The COVID-19 Health Services Disruption Survey 2020 is a series of surveys developed to assess the level of disruption to a range of health services resulting from the COVID-19 global pandemic and subsequent government mandates and changes in behavior to mitigate the spread of the disease.

This survey was conducted in 76 countries using the smartphone-based Premise data collection platform. Respondents were individual members of the general population ages 15-49 years who identified as women. Data were collected from 12,354 respondents. The survey focused on the level of disruption to family planning and reproductive health services and changes in risk of gender-based violence.

The survey was developed specifically to assess the change in levels of service delivery prior to, and immediately following, the onset of the COVID-19 global pandemic. Data generated from this survey is not intended to be used as an overall estimate of the level of health service delivery.

The COVID-19 Health Services Disruption Survey 2020 is a series of surveys developed to assess the level of disruption to a range of health services resulting from the COVID-19 global pandemic and subsequent government mandates and changes in behavior to mitigate the spread of the disease.

This survey was conducted in 76 countries using the smartphone-based Premise data collection platform. Respondents were individual members of the general population who were pregnant or had given birth within the past 6 months at the time of the survey. Data were collected from 2,129 respondents. The survey focused on the level of disruption to the provision of antenatal care and delivery services for pregnant women.

The survey was developed specifically to assess the change in levels of service delivery prior to, and immediately following, the onset of the COVID-19 global pandemic. Data generated from this survey is not intended to be used as an overall estimate of the level of health service delivery.

The COVID-19 Health Services Disruption Survey 2020 is a series of surveys developed to assess the level of disruption to a range of health services resulting from the COVID-19 global pandemic and subsequent government mandates and changes in behavior to mitigate the spread of the disease.

This survey was conducted in 76 countries using the smartphone-based Premise data collection platform. Respondents were individual members of the general population who served as caregiver to at least one child under the age of two years. Data were collected from 7,230 respondents. The survey focused on the level of disruption to the provision of vaccines and general health services for children under the age of two.

The survey was developed specifically to assess the change in levels of service delivery prior to, and immediately following, the onset of the COVID-19 global pandemic. Data generated from this survey is not intended to be used as an overall estimate of the level of health service delivery.

The COVID-19 Health Services Disruption Survey 2020 is a series of surveys developed to assess the level of disruption to a range of health services resulting from the COVID-19 pandemic and subsequent government mandates and changes in behavior to mitigate the spread of the disease.

This survey was conducted in 76 countries using the smartphone-based Premise data collection platform. Respondents were individual members of the general population. Data were collected from 52,492 respondents. The survey focused on the level of disruption to the provision of general health services, including visits to medical providers and access to medication.

The survey was developed specifically to assess the change in levels of service delivery prior to, and immediately following, the onset of the COVID-19 global pandemic. Data generated from this survey is not intended to be used as an overall estimate of the level of health service delivery.

These data were collected and compiled as part of the Improving Methods to Measure Comparable Mortality by Cause (IMMCMC) project, funded by Australia's National Health and Medical Research Council (NHMRC). Verbal autopsies (VAs) were conducted between 2011 and 2014 in three sites: Bohol, Philippines; Chandpur and Comila Districts, Bangladesh; and Central and Eastern Highlands Provinces, Papua New Guinea. Diagnostic criteria and cause lists similar to those employed in the Population Health Metrics Research Consortium (PHMRC) study were used to identify gold standard (GS) deaths. This study added 3512 deaths (2491 adults, 320 children, and 701 neonates) to the GS VA database created from the PHMRC study. This dataset contains the combined PHMRC and IMMCMC data for an updated GS VA database.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

Annual estimates for fertility, population, migration, and all-cause mortality are available from the GBD Results Tool. Estimates are available by age and sex for 1950-2019. Select tables published in The Lancet in October 2020 in "Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019" are also available for download via the “Files” tab above.

For additional GBD results and resources, visit the GBD 2019 Data Resources page.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

Annual estimates for incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life years (DALYs) due to 369 diseases and injuries are available from the GBD Results Tool. Estimates are available by age and sex for 1990-2019. Select tables published in The Lancet in October 2020 in "Global burden of 369 diseases and injuries, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019" are also available for download via the “Files” tab above.

For additional GBD results and resources, visit the GBD 2019 Data Resources page.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

Annual deaths, YLLs, YLDs, and DALYs attributable to 87 risk factors as well as estimates for summary exposure values (SEVs) by risk are available from the GBD Results Tool. Estimates are available by age and sex for 1990-2019. Select tables published in The Lancet in October 2020 in "Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019" are also available for download via the “Files” tab above.

For additional GBD results and resources, visit the GBD 2019 Data Resources page.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

This dataset provides estimates for relative risks due to exposure to particulate matter for ischemic heart disease, stroke, chronic obstructive pulmonary disease, lung cancer, acute lower respiratory infection, type 2 diabetes mellitus, as well as birthweight and gestational age shifts, low birthweight (<2500g), and pre-term births (<37 weeks). The input data used to create the estimates are also provided. These splines are generated using the MR-BRT meta-regression tool and input data from epidemiologic studies of exposure to ambient air pollution, household air pollution from the use of solid fuels, and secondhand tobacco smoke.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

This reference life table, or theoretical minimum risk life table (TMRLT), is used in GBD to calculate years of life lost (YLLs) due to premature mortality. It was constructed based on the lowest observed age-specific mortality rates by location and sex across all estimation years from all locations with populations over 5 million in 2016. YLLs are computed by multiplying the number of estimated deaths by the reference life table’s life expectancy at age of death. The table includes estimates for life expectancy at age x for ages 0 to 95+ at five-year intervals.

For additional GBD results and resources, visit the GBD 2019 Data Resources page.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

Annual estimates for life expectancy and healthy life expectancy (HALE) are available from the GBD Results Tool. Estimates are available by age and sex for 1990-2019.

For additional GBD results and resources, visit the GBD 2019 Data Resources page.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

This dataset provides migration estimates by location, sex, age, and single calendar year for 1950-2019. Data sources used to produce these estimates came from 1,250 censuses and 747 population registry location-years. This dataset provides population estimates for 1950-2019 by the following: location; single calendar year; single year of age; 5-year age group and select custom age aggregates; and sex. Data sources used to produce these estimates came from 1,250 censuses and 747 population registry location-years.

For additional GBD results and resources, visit the GBD 2019 Data Resources page.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

This dataset provides annual estimates for age-specific fertility rate (ASFR), total fertility fate (TFR), total fertility under 25 years (TFU25), net reproductive rate (NRR), live births, and crude birth rate for 1950-2019. Data sources used to produce the ASFR estimates came from 8078 location-years of vital registration data, and 439 complete birth histories and 628 summary birth histories from 938 surveys, 349 censuses, and 238 other sources.

For additional GBD results and resources, visit the GBD 2019 Data Resources page.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

This dataset provides migration estimates by location, sex, age, and single calendar year for 1950-2018. Data sources used to produce these estimates came from 1,250 censuses and 747 population registry location-years.

For additional GBD results and resources, visit the GBD 2019 Data Resources page.

This dataset represents estimates of the ongoing COVID-19 pandemic across the 50 U.S. States and DC through 28th February 2021. Projections for total and daily deaths, daily infections, and testing are included with hospital resource use statistics. In total five scenarios are presented: a 'plausible reference scenario,' which assumes social distancing mandates are re-imposed for 6 weeks when a threshold daily death rate of 8 per million is reached; a 'mandates easing' scenario, where mandates are not re-imposed; a 'universal mask-use' scenario, where mask utilization reaches 95% usage in public in every location; a less comprehensive mask scenario of 85% public use of masks (‘plausible reference + 85% mask-use’ scenario); and a scenario of universal mask wearing in the absence of any additional NPI (‘mandate easing + universal mask use’). These projections are produced with a model that incorporates data on observed COVID-19 deaths, hospitalizations, and cases, as well as multiple covariates.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

This dataset provides annual estimates for under-5 mortality (5q0, or ages 0-4) and adult mortality (45q15, or ages 15-59), as expressed by probability of death, by sex for 1950-2019. For under-5 mortality estimation, 7417 sources were used. These included 28,016 location-years of vital registration data, 481 surveys with complete birth histories, and 1081 sources on summary birth histories. For adult mortality, 7355 sources were used. These included 7000 location-years of vital registration and 322 location-years of sample vital registration, 66 sources of household deaths, 102 censuses, and 133 surveys.

For additional GBD results and resources, visit the GBD 2019 Data Resources page.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

This dataset contains life tables with estimates for life expectancy and probability of death by location, single calendar year, age group, and sex for 1950-2019. The life tables contain both estimates produced including deaths from natural disasters, wars, etc., as well as estimates produced without these types of deaths. Locations covered include both GBD locations and special regions such as World Bank Income Levels. Data used to produce these tables came from vital registration (VR) systems, sample registration systems, household surveys, censuses, disease surveillance, and demographic surveillance systems (DSS).

For additional GBD results and resources, visit the GBD 2019 Data Resources page.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

Developed by GBD researchers and used to help produce these estimates, the Socio-demographic Index (SDI) is a composite indicator of development status strongly correlated with health outcomes. It is the geometric mean of 0 to 1 indices of total fertility rate under the age of 25 (TFU25), mean education for those ages 15 and older (EDU15+), and lag distributed income (LDI) per capita. As a composite, a location with an SDI of 0 would have a theoretical minimum level of development relevant to health, while a location with an SDI of 1 would have a theoretical maximum level.

This dataset provides tables with SDI values for all estimated GBD 2019 locations for 1950–2019, as well as reference SDI quintile values.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

These tables contain International Classification of Diseases (ICD) codes, for both ICD-9 and ICD-10, mapped to GBD 2019 causes of death and nonfatal causes.

For additional GBD results and resources, visit the GBD 2019 Data Resources page.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

Disability weights, which represent the magnitude of health loss associated with specific health outcomes, are used to calculate years lived with disability (YLD) for these outcomes in a given population. The weights are measured on a scale from 0 to 1, where 0 equals a state of full health and 1 equals death. This table provides disability weights for the 440 health states (including combined health states) used to estimate nonfatal health outcomes for the GBD 2019 study.

For additional GBD results and resources, visit the GBD 2019 Data Resources page.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

This dataset includes the following:

  • Relative risks used by age and sex for each outcome for all risk factors except for ambient air pollution, alcohol, smoking, and temperature
  • Relative risks used by age and sex for each outcome for the particulate matter integrated exposure response curve
  • Relative risks used by age and sex for each outcome for alcohol use globally
  • Relative risks used by age and sex for each outcome for smoking globally

For additional GBD results and resources, visit the GBD 2019 Data Resources page.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

This set of files contain the following for GBD 2019: the cause hierarchy; the risk, impairment, etiology, and injury n-code (REI) hierarchy; and locations hierarchies. The GBD Locations Hierarchy file contains only GBD locations, including subnational locations for which results were released at the time of the study's publication. (Locations will be added as additional subnational results are released.) The All Locations Hierarchies file also includes hierarchies for other regions for which estimates were produced, such as WHO and World Bank regions. These files allow users to filter for sets of values by level or parent category, including cause or risk group, GBD super region or region, or custom region.

The Global Burden of Disease Study 2019 (GBD 2019), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

Covariates, which are independent variables with a positive or negative relationship to GBD diseases and conditions, are used to inform the estimation process in models in all components and stages of the GBD study. Types of covariates used include socioeconomic, demographic, health system access, climate, and food consumption. This dataset contains data for 771 covariates for 1980-2019 used in the GBD 2019 study.

Get Data Files

For additional GBD results and resources, visit the GBD 2019 Data Resources page.

This dataset is the result of a study to quantify health-care spending attributable to modifiable risk factors in the United States of America for 2016. Data from two existing studies were used to produce the estimates. The first dataset is the Institute for Health Metrics and Evaluation’s Disease Expenditure Study 2016, from which estimates of US health-care spending by condition, age, and sex were extracted. These results were merged with population attributable fraction estimates for 84 modifiable risk factors from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017. Estimates were produced for spending by 14 aggregate conditions attributable to 19 risk factors. The estimates are by sex and 5 age groups and reported in 2016 US dollars.

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. 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

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