IHME Data
Download datasets created by IHME for our research projects and publications. You can learn more about our research and publications on our website
Data made available for download on IHME Websites can be used, shared, modified or built upon by non-commercial users in accordance with the IHME FREE-OF-CHARGE NON-COMMERCIAL USER AGREEMENT. For more information (and inquiries about commercial use), visit IHME Terms and Conditions.
The Global Burden of Disease Study 2017 (GBD 2017), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories, and at the subnational level for a subset of countries.
This dataset includes full and abridged life tables with estimates for life expectancy and probability of death by location, single calendar year, age, and sex for 1950-2017. Full life tables contain estimates by single year of age. Abridged life tables contain estimates by 5-year age group. 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).
The Global Burden of Disease Study 2017 (GBD 2017), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories, and at the subnational level for a subset of countries. These tables contain International Classification of Diseases (ICD) codes, for both ICD-9 and ICD-10, mapped to GBD 2017 causes of death and nonfatal causes.
The Global Burden of Disease Study 2017 (GBD 2017), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories, and at the subnational level for a subset of countries.
This set of files contain the following for GBD 2017: 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 2017 (GBD 2017), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories, and at the subnational level for a subset of countries.
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 dataset provides disability weights for the 234 unique health states used to estimate nonfatal health outcomes for the GBD 2017 study. The data were published in The Lancet in November 2018 in "Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017."
The Global Burden of Disease Study 2017 (GBD 2017), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
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 334 covariates for 1980-2017 used in the GBD 2017 study.
IHME and collaborating researchers conducted a study to map the global distribution of genotypes of bacterial strains that cause tuberculosis disease and examine whether any epidemiologically relevant clinical characteristics were associated with those genotypes. They performed a systematic review to create a comprehensive dataset of human TB molecular epidemiology studies that used representative sampling techniques. Data were extracted and synthesized from 206 studies that reported prevalence of bacterial genotypes (representing over 200,000 bacterial isolates collected over 27 years in 85 countries) and from 34 studies that reported clinical characteristics associated with those genotypes. This dataset contains the following: a screening sheet detailing all studies reviewed; raw genotype distribution data extracted in the systematic review; raw genetic clustering data extracted; and sheets containing MTBC genotype conversions for all genotyping methods included in this study.
IHME researchers leveraged data from the Global Burden of Disease (GBD) study to produce life expectancy, all-cause mortality, and cause-specific mortality forecasts for 195 countries and territories from 2016-2040. In addition to reference scenarios, alternative “better” and “worse” scenarios were produced. Estimates for life expectancy at birth, and deaths and years of life lost (YLLs) for 250 causes by cause, age, and sex are available from GBD Foresight. Estimates for deaths and YLLs attributable to each GBD risk factor and summary exposure values (SEV) by risk are also available. Select tables published in The Lancet in October 2018 in "Forecasting life expectancy, years of life lost, and all-cause and cause-specific mortality for 250 causes of death: reference and alternative scenarios for 2016–40 for 195 countries and territories" are available for download in this record.
Human capital, widely recognized as the level of education and health in a population, is considered an important determinant of economic growth. IHME generated a measure of expected human capital, defined for each birth cohort as the expected years lived from 20 to 64 years of age adjusted for educational attainment, learning or education quality, and functional health status using period-age-and-sex-specific rates. Learning estimates are based on student performance on math, science, and reading assessments. Functional health status is comprised of the prevalence of seven conditions with proven links to productivity and learning.
This dataset includes estimates for the following five measures by age and sex for 195 countries from 1990-2016: expected human capital; average years of educational attainment, from 0-18 years; learning, the average standardized test score transformed to a 0 to 1 scale; health, transformed to a 0 to 1 scale; and survival, or expected years lived between ages 20-64.
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 in 52 countries in Africa between 2000-2015. These estimates were produced using data on diarrhea and geographical locations from censuses, several household survey series, including the Demographic and Health Survey (DHS) and Multiple Indicator Cluster Survey (MICS), and other country‐specific surveys.
This dataset includes the following:
- GeoTIFF raster files for pixel-level estimates of diarrhea prevalence, incidence of severe diarrheal episodes, diarrhea-related mortality, annualized rates of change for severe incidence and diarrheal mortality, and the probability that a unit will reach GAPPD goals for the reduction of incidence and mortality for given years
- CSV files of aggregated estimates for each country at the first and second administrative divisions
- Code files used to generate the estimates
Research by IHME and the Department of Health Surveillance, Brazil Ministry of Health produced estimates for age-standardized mortality rates by Brazil municipality for HIV/AIDS and tuberculosis. The estimates were generated using de-identified death records from the Brazil Mortality Information System (SIM); case notification data from the Brazil national notification system (SINAN); standardization of vital registration of data based on GBD 2016 methodology; and the application of small area estimation models.
This dataset provides estimates for age-standardized mortality rates by cause and sex at the state level and the municipality level for each state for 2001-2015. Study results were published in BMC Medicine in September 2018 in "Progress toward eliminating TB and HIV deaths in Brazil, 2001–2015: a spatial assessment."
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
Estimates for alcohol use and the burden attributable to this risk factor were produced by sex, age group, and year for 195 countries and territories for 1990-2016. Estimates for alcohol-attributable deaths and disability-adjusted life-years (DALYs) are available from the GBD Results Tool. Files available in this record include estimates of the prevalence of current drinking, abstention, and the population average of standard drinks daily. Study results were published in The Lancet in August 2018 in "Alcohol use and burden: a systematic analysis from the Global Burden of Disease Study 2016 for 195 countries and territories, 1990–2016."
Contemporary range maps for 278 medically important snake species and estimates of the populations most vulnerable to snakebite envenoming were produced. Existing expert opinion range (EOR) maps, occurrence data, and a multivariate environmental similarity analysis were used to generate the contemporary range maps. These data were triangulated with geographical accessibility surfaces, the HAQ Index (a measure of healthcare access and quality), and information on antivenom availability to identify vulnerable populations.
This dataset includes: shapefiles for the range maps and vulnerable population counts; GeoTIFF files at the 5x5 km-level for venomous snake species ranges, vulnerable population hotspots, and travel time to major cities in snake species ranges; and CSV files for vulnerable populations at the admin 2-level.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
Estimates for deaths, disability-adjusted life years (DALYs), years lived with disability (YLDs), years of life lost (YLLs), prevalence, and incidence for 29 cancer groups by age and sex for 1990-2016 are available from the GBD Results Tool. Files available in this record are the web tables published in JAMA Oncology in June 2018 in "Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-years for 29 Cancer Groups, 1990 to 2016."
Global Burden of Disease Study 2016 (GBD 2016) estimates were used in an analysis of personal healthcare access and quality for 195 countries and territories, as well as selected subnational locations, over time. This dataset includes the following global, regional, national, and selected subnational estimates for 1990-2016: age-standardized risk-standardized death rates from 24 non-cancer causes considered amenable to healthcare; age-standardized mortality-to-incidence ratios for 8 cancers considered amenable to healthcare; and the Healthcare Access and Quality (HAQ) Index and individual scores for each of the 32 causes on a scale of 0 to 100. Code used to produce the estimates is also included.
Results were published in The Lancet in May 2018 in "Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016."
Research by the Global Burden of Disease Health Financing Collaborator Network produced projected health spending estimates for 2016-2040 for 188 countries. The estimates cover total health spending, and health spending disaggregated by source into government spending, out-of-pocket, prepaid private, and development assistance for health. GDP and all-sector government spending were extracted for 1980–2015 and used with retrospective health spending estimates for 1995-2015 to forecast GDP, all-sector government spending, and health spending through 2040. Results of the study were published in The Lancet in April 2018 in "Trends in future health financing and coverage: future health spending and universal health coverage in 188 countries, 2016–2040."
Research by the Global Burden of Disease Health Financing Collaborator Network estimated HIV/AIDs spending for 188 countries for 2000-2015. The estimates cover HIV/AIDS spending disaggregated by source into government spending, out-of-pocket, prepaid private, and development assistance for health. Spending is also disaggregated by function, including care and treatment, prevention, and other spending. HIV/AIDS spending by source and function was estimated based on a diverse set of data, including country reports, National AIDS Spending Assessments, and National Health Accounts. Development assistance for health data was sourced from budgets, project records, and financial statements. Results of the study were published in The Lancet in April 2018 in "Spending on health and HIV/AIDS: domestic health spending and development assistance in 188 countries, 1995-2015."
Research by the Global Burden of Disease Health Financing Collaborator Network produced retrospective national health spending estimates for 1995-2015 for 188 countries. The estimates cover total health spending, and health spending disaggregated by source into government spending, out-of-pocket, prepaid private, and development assistance for health. National health spending by source, including development assistance for health, was estimated based on a diverse set of data, including program reports, budget data, national estimates, and National Health Accounts. The resulting estimates were used to help produce prospective health spending estimates for 2016-2040. Results of the analysis were published in The Lancet in April 2018 in "Spending on health and HIV/AIDS: domestic health spending and development assistance in 188 countries, 1995-2015."
This version of the Development Assistance for Health (DAH) Database includes estimates for 1990-2017, 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 2017 are a program area disaggregation within the tuberculosis health focus area, and identification of DAH targeting pandemic preparedness, within the HSS/SWAps health focus area. Also new this year are the tracking of the United Arab Emirates as a source of funding and tracking Unitaid channel funding.
To understand the framework used to track DAH, users of the database should review IHME's Financing Global Health 2017 report and methods annex.
This survey was conducted as part of the Gavi Full Country Evaluation (FCE) project in Zambia. Gavi FCEs are prospective studies covering the period 2013-2016 that aim to assess the barriers to and drivers of immunization program performance. The Zambia FCE Health Facility Survey was conducted in 22 districts purposely selected to overlap with those where a baseline facility survey for the Access, Bottlenecks, Costs, and Equity (ABCE) Project in Zambia was performed. The districts provide a geographically and demographically representative sample of Zambia’s health system. For this survey, data on financing, staffing, facility procedures and guidelines, vaccine stocks, and supply delivery (including cold chain temperature measurements) were collected from a representative sample of 171 health facilities. Data were collected through interviews of health providers, direct observation of facility areas, and assisted observation of immunization sessions.
IHME research produced estimates for age-standardized mortality rates by county from lower respiratory infections (LRIs), diarrheal diseases, HIV/AIDS, meningitis, hepatitis, and tuberculosis. The estimates were generated using de-identified death records from the National Center for Health Statistics (NCHS); population counts from the U.S. Census Bureau, NCHS, and the Human Mortality Database; the cause list from the Global Burden of Disease Study (GBD); and the application of small area estimation models. This dataset provides estimates for age-standardized mortality rates by cause and sex at the county level for each state, the District of Columbia, and the United States as a whole for 1980-2014. Also included are changes in rates during this period and counties with the highest and lowest mortality rates for each cause in 2014. Study results were published in JAMA in March 2018 in "Trends and patterns of differences in infectious disease mortality among US counties, 1980–2014."
The Access, Bottlenecks, Costs, and Equity (ABCE) project is a multipronged and multicountry research collaboration focused on understanding what drives and hinders health service provision. Two datasets resulting from the ABCE project in the Indian state of Tamil Nadu are available for download. This first contains results of a health facility survey which gathered information on services offered, expenditure, revenue, personnel by category, equipment, capacity, and other variables related to facility operations. In total, a nationally representative sample of 168 facilities were surveyed. Data were collected through interviews of health providers, direct observation of facility areas, and assisted observation of facility resources. The second dataset includes information collected in patient exit interviews conducted after patients visited facilities in the ABCE sample.
The Access, Bottlenecks, Costs, and Equity (ABCE) project is a multipronged and multicountry research collaboration focused on understanding what drives and hinders health service provision. Two datasets resulting from the ABCE project in the Indian state of Odisha are available for download. This first contains results of a health facility survey which gathered information on services offered, expenditure, revenue, personnel by category, equipment, capacity, HIV/AIDS care, and other variables related to facility operations. In total, a nationally representative sample of 108 facilities were surveyed. Data were collected through interviews of health providers, direct observation of facility areas, and assisted observation of facility resources. The second dataset includes information collected in patient exit interviews conducted after patients visited facilities in the ABCE sample.
The Access, Bottlenecks, Costs, and Equity (ABCE) project is a multipronged and multicountry research collaboration focused on understanding what drives and hinders health service provision. Two datasets resulting from the ABCE project in the Indian state of Madhya Pradesh are available for download. This first contains results of a health facility survey which gathered information on services offered, expenditure, revenue, personnel by category, equipment, capacity, vaccines, and other variables related to facility operations. In total, a nationally representative sample of 203 facilities were surveyed. Data were collected through interviews of health providers, direct observation of facility areas, and assisted observation of facility resources. The second dataset includes information collected in patient exit interviews conducted after patients visited facilities in the ABCE sample.
The Access, Bottlenecks, Costs, and Equity (ABCE) project is a multipronged and multicountry research collaboration focused on understanding what drives and hinders health service provision. Two datasets resulting from the ABCE project in the Indian state of Gujarat are available for download. This first contains results of a health facility survey which gathered information on services offered, expenditure, revenue, personnel by category, equipment, capacity, vaccines, and other variables related to facility operations. In total, a nationally representative sample of 103 facilities were surveyed. Data were collected through interviews of health providers, direct observation of facility areas, and assisted observation of facility resources. The second dataset includes information collected in patient exit interviews conducted after patients visited facilities in the ABCE sample.
The Access, Bottlenecks, Costs, and Equity (ABCE) project is a multipronged and multicountry research collaboration focused on understanding what drives and hinders health service provision. Two datasets resulting from the ABCE project in the Indian state of Andhra Pradesh (now Andhra Pradesh and Telangana) are available for download. This first contains results of a health facility survey which gathered information on services offered, expenditure, revenue, personnel by category, equipment, capacity, HIV/AIDS care, and other variables related to facility operations. In total, a nationally representative sample of 98 facilities were surveyed. Data were collected through interviews of health providers, direct observation of facility areas, and assisted observation of facility resources. The second dataset includes information collected in patient exit interviews conducted after patients visited facilities in the ABCE sample.
IHME research produced estimates for age-standardized mortality rates by county from alcohol use disorders, drug use disorders, self-harm, and interpersonal violence. The estimates were generated using de-identified death records from the National Center for Health Statistics (NCHS); population counts from the U.S. Census Bureau, NCHS, and the Human Mortality Database; the cause list from the Global Burden of Disease Study (GBD); and the application of small area estimation models. This dataset provides estimates for age-standardized mortality rates by cause and sex at the county level for each state, the District of Columbia, and the United States as a whole for 1980-2014. Also included are changes in rates during this period and counties with the highest and lowest mortality rates for each cause in 2014. Study results were published in JAMA in March 2018 in "Trends and patterns of geographic variation in mortality from substance use disorders and intentional injuries among US counties, 1980–2014."
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 at 86 facilities in Umgungundlovu district in KwaZulu-Natal province and Pixley ka Seme district in Northern Cape province. The survey was based on based on the WHO package of essential NCD interventions and South Africa’s Essential Medicine List and Standard Treatment Guidelines for Primary Health Care 2014. It was adapted from a questionnaire created for the Access, Bottlenecks, Costs, and Equity (ABCE) study. 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).
Estimates were produced for under-5 stunting, wasting, and underweight prevalence at the 5x5 km-level in 51 countries in Africa between 2000-2015. These estimates were produced using individual-level height, weight, and age data for children under 5 and geographical locations from household survey series including the Demographic and Health Survey (DHS), Mulitple Indicator Cluster Survey (MICS), Living Standards Measurement Study (LSMS), and Core Welfare Indicators Questionnaire Survey (CWIQ). This dataset includes both GeoTIFF raster files for pixel-level estimates of under-5 stunting, wasting, and underweight prevalence, along with relative annualized rates of change for each, and CSV files of aggregated estimates for each country at the first and second administrative divisions.
Code files used to generate the estimates are available online.
Estimates were produced for average years of educational attainment for women of reproductive age (15-49), women ages 20-24, and equivalent male age groups at the 5x5 km-level in 51 countries in Africa between 2000-2015. Estimates were also generated for the disparity in years of attainment between males and females for the same ages and period. These estimates were produced using data on educational attainment and geographical locations from censuses, several household survey series, including the Demographic and Health Survey (DHS) and Multiple Indicator Cluster Survey (MICS), and other country‐specific surveys. This dataset includes both GeoTIFF raster files for pixel-level estimates of educational attainment and attainment disparity and CSV files of aggregated estimates for each country at the first and second administrative divisions.
Code files used to generate the estimates are available online.
The Child Growth Failure Visualization is an interactive data tool that shows levels and trends in growth failure at birth and in children under 5, both past and projected from 1990 to 2030. The tool also demonstrates how cases of child growth failure (stunting, wasting, and underweight) have changed due to contributing factors including population growth, Socio-demographic Index, and unsafe sanitation from 1990 to 2016 and 2000 to 2016.
This dataset contains the input data used to produce the estimates visualized by the tool. Each file includes information about how the input sources were used and relevant metadata about the sources as suggested in the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER).
Estimates were produced for three stages underlying the potential of widespread epidemics for four viral hemorrhagic fevers (VHFs) in Africa: Ebola virus disease, Marburg virus disease, Lassa fever, and Crimean-Congo hemorrhagic fever. Stage 1, index case potential, assesses populations at risk of infection due to spillover from zoonotic hosts or vectors, identifying where index cases could present. Stage 2, outbreak potential, measures potential for secondary spread amongst humans within specific communities. Stage 3, epidemic potential, evaluates possible spread of local outbreaks nationally, regionally, and internationally. Estimates were generated at the second national administrative division (admin 2) level and as indices on a 0-10 scale, with 10 representing the worst outcome. This dataset includes these estimates in shapefiles and CSV files for admin 2 locations across Africa for each pathogen in each stage.
Estimates were produced for under‐5 mortality (the probability of death before reaching age 5) and neonatal mortality (probability of death within first month of life) for each pixel cell (approximately 5x5 kilometer (km)) in 46 countries in Africa for 1998-2002, 2003-2007, 2008-2012, and 2013-2017. These estimates were produced using data on child mortality and geographical locations from censuses and several household survey series, including the Demographic and Health Survey (DHS), Unicef Mulitple Indicator Cluster Survey (MICS), and other country‐specific surveys. This dataset includes both GeoTIFF raster files for pixel-level estimates of probability of death and CSV files of aggregated estimates for each country at the first and second administrative divisions.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
Estimates for deaths, YLLs, YLDs, and DALYs attributable to 84 risk factors by age and sex as well as estimates for summary exposure values (SEVs) by risk are available from the GBD Results Tool for 1990-2016 (5-year intervals). This record contains select tables published in The Lancet in September 2017 in "Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016.".
For additional GBD results and resources, visit the GBD 2016 Data Resources page.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
Estimates for disability-adjusted life years (DALYs) by cause, age, and sex and healthy life expectancy (HALE) by age and sex are available from the GBD Results Tool for 1990-2016. Select tables published in The Lancet in September 2017 in "Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016" are also available in this record.
For additional GBD results and resources, visit the GBD 2016 Data Resources page.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
Estimates for incidence, prevalence, and years lived with disability (YLDs) are available from the GBD Results Tool. Estimates are available by age and sex for 328 causes for 1990-2016 (quinquennial). Select tables published in The Lancet in September 2017 in "Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016" are also available for download via the “Files” tab above.
For additional GBD results and resources, visit the GBD 2016 Data Resources page.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
Cause-specific mortality estimates for deaths and years of life lost (YLLs) are available from the GBD Results Tool. Estimates are available by age and sex for 264 causes for 1990-2016. Select tables published in The Lancet in September 2017 in "Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the Global Burden of Disease Study 2016" are also available for download via the “Files” tab above.
For additional GBD results and resources, visit the GBD 2016 Data Resources page.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
Estimates of life expectancy and all-cause mortality, including under-5 mortality, are available from the GBD Results Tool. Estimates are available by age, sex, and location for 1990-2016. Select tables published in The Lancet in September 2017 in "Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970-2016: a systematic analysis for the Global Burden of Disease Study 2016” are also available for download via the “Files” tab above.
For additional GBD results and resources, visit the GBD 2016 Data Resources page.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors from 1990 to 2016.
The United Nations established, in September 2015, the Sustainable Development Goals (SDGs), which specify 17 universal goals, 169 targets, and 232 indicators leading up to 2030. Drawing from GBD 2016, this dataset provides estimates for 37 health-related SDG indicators for 188 countries from 1990 to 2016, as well as projections, based on past trends, from 2017 to 2030. These 37 SDG indicators were used to construct the health-related SDG index, a summary measure of overall performance across the health-related SDGs.
The results were published in The Lancet in September 2017 in "Measuring progress and projecting attainment based on past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016."
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
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 dataset provides disability weights for the 235 unique health states used to estimate nonfatal health outcomes for the GBD 2016 study. The data were published in The Lancet in September 2017 in "Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016."
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
This set of location hierarchy files contains the GBD 2016 reporting hierarchy for the full set of locations estimated for the study, including all subnational locations. It also includes the hierarchy for the set of locations for which results are available in the GBD Results Tool, and data visualizations such as GBD Compare, as of September 2017. (Please note that this latter hierarchy will change as results for additional subnational results are released.) These files files can help users aggregate GBD 2016 results by GBD super region and region, Socio-demographic Index (SDI) grouping, and other location levels.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries. These tables contain International Classification of Diseases (ICD) codes, for both ICD-9 and ICD-10, mapped to GBD 2016 causes of death and nonfatal causes.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
This dataset provides population estimates by location, age, and sex for 1950-2016. Data sources used to produce these estimates include World Population Prospects: 2015 Revision, from the United Nations Population Division, and the WHO Human Mortality Database.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
Developed by GBD researchers and used to help produce these estimates, the Socio-demographic Index (SDI) is a summary measure of a geography's socio-demographic development. It is based on average income per person, educational attainment, and total fertility rate (TFR). SDI contains an interpretable scale: zero represents the lowest income per capita, lowest educational attainment, and highest TFR observed across all GBD geographies from 1970 to 2016, and one represents the highest income per capita, highest educational attainment, and lowest TFR. This dataset provides tables with SDI values for all estimated GBD 2016 geographies for 1970–2016 and groupings by geography based on 2016 values.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
In GBD, an essential stage in the process for producing estimates for adult mortality rates (or 45q15, the probability of death between exact ages 15 and 60) involves assessing the completeness of adult death reporting from vital registration and censuses. In this evaluation, raw data points from vital registration and sample registration are adjusted using formal demographic techniques called death distribution methods (DDM) and then smoothed to generate full time-series estimates of adult death reporting completeness. This dataset contains a list of data input sources used in the generation of DDM estimates for adult mortality.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
This reference life table is used in GBD to calculate years of life lost (YLLs). It was constructed based on the lowest estimated age-specific mortality rates from all locations with populations over 5 million in the 2015 iteration of GBD. 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 the probability of death within an age range, the proportion of the hypothetical cohort still alive at age x, and life expectancy at age x for ages 0 to 110+ at five-year intervals.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
Covariates, which are independent variables with a positive or negative relationship to GBD diseases and conditions, are used to inform the estimation process in all models of the GBD study. Types of covariates used include socioeconomic, demographic, health system access, climate, and food consumption. This dataset contains data for 565 covariates for 1980-2016 used in the GBD 2016 study. Please note that data for England is not included for some covariates.
Data files are available to download at this location.
Research by the Global Burden of Disease Health Financing Collaborator Network produced forecasted health spending estimates for 2015-2040 for 184 countries. The estimates cover total health spending, and health spending disaggregated by source into government spending, out-of-pocket, prepaid private, and development assistance for health. GDP and all-sector government spending were extracted for 1980–2015 and used with retrospective health spending estimates for 1995-2014 to forecast GDP, all-sector government spending, and health spending through 2040. Results of the study were published in The Lancet in April 2017 in "Future and potential spending on health 2015–40: government, prepaid private, out-of-pocket, and donor financing in 184 countries."
Research by the Global Burden of Disease Health Financing Collaborator Network produced retrospective national health spending estimates for 1995-2014 for 184 countries. The estimates cover total health spending, and health spending disaggregated by source into government spending, out-of-pocket, prepaid private, and development assistance for health. National health spending by source, including development assistance for health, was estimated based on a diverse set of data, including program reports, budget data, national estimates, and 964 National Health Accounts. The resulting estimates were used to help produce forecasted health spending estimates for 2015-2040. Results of the study were published in The Lancet in April 2017 in "Evolution and patterns of global health financing 1995–2014: development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries."
This update of the Development Assistance for Health (DAH) Database includes estimates for 1990-2016, 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 funding agency, country and geographic region, and health focus area. New in 2016 is a program area disaggregation within malaria health focus areas.
To understand the framework used to track DAH, users of the DAH Database 1990-2016 should review IHME's Financing Global Health 2016 technical report and methods annex.
IHME research produced estimates on US health care spending by age, sex, condition, and type of care, from 1996 through 2013, for children and adolescents ages 19 years and younger. Government budgets, insurance claims, facility surveys, household surveys, and official US records for the period were collected and combined. In total, 183 sources of data were used to estimate spending for 155 conditions. For each record, spending was extracted, along with the age and sex of the patient, and the type of care. Study results were published in JAMA Pediatrics in December 2016 in “Spending on Children’s Personal Health Care in the United States, 1996-2013.”
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