Embedded Files
GBD Compare: Analyze updated estimates of the world’s health for 369 diseases and injuries and 87 risk factors from 1990 to 2019 in this interactive tool. Use maps and treemaps, arrow diagrams, and many other charts to compare causes and risks within a country, compare countries with regions or the world, and explore patterns and trends by country, age, and sex. Results at the subnational level are also available for select countries. Drill down from a global view into specific details. Compare expected and observed trends. Watch how disease patterns have changed over time. Learn which causes of death and disability are having more impact and which are waning.
Burden of Proof: The Burden of Proof tool shows the strength of evidence between health risks and outcomes, indicating the likelihood of certain behaviors to have an impact on health. The tool uses a novel star-rating system to rank each pair from one to five, based on both the magnitude of risk shown by studies to date, as well as the consistency of findings between those studies.
Population Forecasting: Population estimates by age, sex, and location for 1950-2100.
GHDx: GBD Sources Tool: Examine the input data used to create estimates for GBD 2021.
GBD Results Tool: Download the estimates directly from the GBD
Modeling tools:
MortViz: is the visual overlay for all-cause mortality analysis for 5q0 (probability of death between birth and age 5) and 45q15 (probability of death between age 15 and 60 years). Best used to explore the input data, modeling steps/ effects, and final results for child and adult mortality.
CoDViz: is the visual overlay for CODEm (the cause of death ensemble model) that is used to estimate cause-specific mortality for GBD diseases and injuries. Best used to look at the input data for each cause-specific mortality model as well as the effects of all of the data processing steps
EpiViz: With this interactive tool, you can explore data inputs and epidemiological estimates from the GBD 2021 project. The majority of diseases, injuries, and risk factors were modeled using DisMod-MR 2.1, a Bayesian mixed-effects meta-regression modeling tool developed for GBD analyses. Initial estimates are made at the global level then sequentially revised down to the national and subnational levels using data that are progressively more detailed with respect to geography and time.
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