Key Takeaways
- 8.8 million deaths in 2019 were due to air pollution (2.9 million from outdoor air pollution and 5.9 million from household air pollution), worldwide
- 9.2 million deaths in 2019 were attributable to diabetes globally
- 2.0 million deaths in 2019 were attributable to road traffic injuries globally
- Stroke caused 6.55 million deaths in 2019 globally (WHO)
- Tuberculosis caused 1.4 million deaths in 2019 globally (WHO)
- Malaria caused 409,000 deaths in 2019 in WHO’s World Malaria Report estimates (WHO fact sheet)
- Globally, in 2019, chronic kidney disease caused 1.3 million deaths (IHME GBD)
- In 2021, 675,000 US deaths were attributed to cancer (CDC)
- In 2021, 52,000 US deaths were attributed to influenza and pneumonia (CDC)
- 201,000 maternal deaths occurred globally in 2020 (WHO/UNFPA/World Bank maternal mortality estimates via World Bank indicator SH.STA.MMRT)
- In 2021, 13.6 million people fell ill with tuberculosis (WHO Global TB Report 2022)
- In 2022, 12.0 million people with TB did not receive treatment (WHO Global Tuberculosis Report 2023 estimate)
- Across 191 countries, excess mortality estimates for 2020–2021 averaged 17 excess deaths per 10,000 people (The Lancet modeling)
- COVID-19 accounted for about 14.9% of all deaths worldwide in 2021, based on excess mortality estimates by The Economist/WHO modeling
- In Italy, excess mortality in 2020 was estimated at 136,000 deaths above expected (ISTAT)
Worldwide, air pollution, major NCDs, and injuries drive millions of deaths while progress in child survival continues.
Related reading
Global Burden
Global Burden Interpretation
Mortality Rates
Mortality Rates Interpretation
More related reading
Cause Specific
Cause Specific Interpretation
Healthcare Access
Healthcare Access Interpretation
More related reading
Excess Mortality
Excess Mortality Interpretation
Regional Differences
Regional Differences Interpretation
More related reading
Risk & Patterns
Risk & Patterns Interpretation
Policy & Health Systems
Policy & Health Systems Interpretation
More related reading
Data & Methods
Data & Methods Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Leah Kessler. (2026, February 13). Mortality Statistics. Gitnux. https://gitnux.org/mortality-statistics
Leah Kessler. "Mortality Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/mortality-statistics.
Leah Kessler. 2026. "Mortality Statistics." Gitnux. https://gitnux.org/mortality-statistics.
References
- 1who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health
- 2who.int/news-room/fact-sheets/detail/diabetes
- 3who.int/news-room/fact-sheets/detail/road-traffic-injuries
- 5who.int/news-room/fact-sheets/detail/drowning
- 6who.int/news-room/fact-sheets/detail/household-air-pollution-and-health
- 7who.int/news-room/fact-sheets/detail/stroke
- 8who.int/news-room/fact-sheets/detail/tuberculosis
- 9who.int/news-room/fact-sheets/detail/malaria
- 10who.int/news-room/fact-sheets/detail/hiv-aids
- 23who.int/data/gho/data/themes/road-safety
- 28who.int/publications/i/item/9789240061729
- 29who.int/publications/i/item/9789240071315
- 32who.int/news-room/fact-sheets/detail/child-mortality
- 33who.int/news-room/fact-sheets/detail/newborn-mortality
- 39who.int/news-room/fact-sheets/detail/drinking-water
- 40who.int/news-room/fact-sheets/detail/air-pollution
- 41who.int/news-room/fact-sheets/detail/tobacco
- 4gco.iarc.fr/today/data/factsheets/cancers/15-Lung-fact-sheet.pdf
- 11cdc.gov/nchs/data/nvsr/nvsr73/nvsr73-06.pdf
- 12cdc.gov/nchs/fastats/deaths.htm
- 13cdc.gov/nchs/data/databriefs/db456.pdf
- 14cdc.gov/nchs/data/nvsr/nvsr72/nvsr72-01.pdf
- 19cdc.gov/nchs/data/databriefs/db517.pdf
- 25cdc.gov/nchs/fastats/cancer.htm
- 26cdc.gov/nchs/fastats/flu.htm
- 44cdc.gov/nchs/data/vsrr/vsrr025.pdf
- 15data.worldbank.org/indicator/SP.DYN.LE00.IN
- 16data.worldbank.org/indicator/SP.DYN.CDRT.IN
- 27data.worldbank.org/indicator/SH.STA.MMRT
- 17data.unicef.org/topic/child-survival/neonatal-mortality/
- 18data.unicef.org/topic/child-survival/under-five-mortality/
- 22data.unicef.org/resources/datasets/under-five-mortality/
- 31data.unicef.org/topic/child-health/immunization/
- 43data.unicef.org/topic/maternal-health/delivery-care/
- 20www150.statcan.gc.ca/n1/daily-quotidien/240126/dq240126b-eng.htm
- 21stat.go.jp/english/data/jinsui/index.html
- 24vizhub.healthdata.org/gbd-results/
- 30washdata.org/data/household
- 34thelancet.com/journals/lancet/article/PIIS0140-6736(22)00593-5/fulltext
- 45thelancet.com/pdfs/journals/lancet/PIIS0140-6736(22)01529-8.pdf
- 35economist.com/graphic-detail/covid-pandemic-excess-mortality-tracker
- 36istat.it/it/archivio/264651
- 37ghdx.healthdata.org/gbd-results-tool
- 38childmortality.org/data/under-five
- 42apps.who.int/nha/database/ViewData/Indicators/en







