Subnational mortality estimates for India in 2019: a baseline for evaluating excess deaths due to the COVID-19 pandemic
Open accessAbstract
Background: Estimates of excess mortality are required to assess and compare the impact of the COVID-19 pandemic across populations. For India, reliable baseline prepandemic mortality patterns at national and subnational level are necessary for such assessments. However, available data from the Civil Registration System (CRS) is affected by incompleteness of death recording that varies by sex, age and location. Methods: Under-reporting of CRS 2019 deaths was assessed for three age groups (< 5 years, 15–59 years and ≥60 years) at subnational level, through comparison with age-specific death rates from alternate sources. Age-specific corrections for under-reporting were applied to derive adjusted death counts by sex for each location. These were used to compute life expectancy (LE) at birth by sex in 2019, which were compared with subnational LEs from the Global Burden of Disease (GBD) 2019 Study. Results: A total of 9.92 million deaths (95% UI 9.70 to 10.02) were estimated across India in 2019, about 2.28 million more than CRS reports. Adjustments to under-five and elderly mortality accounted for 30% and 56% of additional deaths, respectively. Adjustments in Bihar, Jharkhand, Madhya Pradesh, Maharashtra, Rajasthan and Uttar Pradesh accounted for 75% of all additional deaths. Adjusted LEs were below corresponding GBD estimates by ≥2 years for males at national level and in 20 states, and by ≥1 year for females in 12 states. Conclusions: These results represent the first-ever subnational mortality estimates for India derived from CRS reported deaths, and serve as a baseline for assessing excess mortality from the COVID-19 pandemic. Adjusted life expectancies indicate higher mortality patterns in India than previously perceived. Under-reporting of infant deaths and those among women and the elderly is evident in many locations. Further CRS strengthening is required to improve the empirical basis for local mortality measurement across the country.
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A number of calculations lead to estimates of death registration completion of around 80%.
“A number of calculations lead to estimates of death registration completion of around 80% [17, 20, 22].”
From Estimates of pandemic excess mortality in India based on civil registration data (2022) · cites this paper as [20]
There is uncertainty about baseline levels of mortality and registration completion in India.
“There is uncertainty about baseline levels of mortality and registration completion [17, 20–22].”
From Estimates of pandemic excess mortality in India based on civil registration data (2022) · cites this paper as [20]
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- Authors
- Rao, C., John, A. J., Yadav, A. K., & Siraj, M.
- Affiliations
- Australian National University (AU)
- International Institute for Population Sciences (IN)
- Deutsche Gesellschaft für Internationale Zusammenarbeit (PH)
- University of California, Berkeley (US)
- Corresponding author
- Rao, Chalapati
- Venue
- BMJ Global Health
- Publisher
- BMJ
- Published
- 2021-11
- Volume
- 6
- Issue
- 11
- Pages
- e007399
- ISSN
- 2059-7908 (ISSN-L)
- PMC
- PMC8627370
- OpenAlex
- W3215672415
- Cited by
- 7
- References
- 24
- Citations by year
- 2025: 1 · 2023: 3 · 2022: 3
- FWCI
- 2.36
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMJ Global Health (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Demography › Insurance, Mortality, Demography, Risk Management
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Physical Sciences › Mathematics › Statistics and Probability › Census and Population Estimation
- Keywords
- excess mortality, COVID-19 pandemic, baseline mortality, civil registration, life expectancy, infant mortality, elderly mortality, sex differences in mortality, India
- MeSH terms
- Global Burden of Disease, COVID-19, SARS-CoV-2, Aged, Child, Preschool, Female, Humans, India, Infant, Infant, Newborn, Male, Pandemics
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