All-cause mortality during the COVID-19 pandemic in Chennai, India: an observational study
Open accessAbstract
BACKGROUND: India has been severely affected by the ongoing COVID-19 pandemic. However, due to shortcomings in disease surveillance, the burden of mortality associated with COVID-19 remains poorly understood. We aimed to assess changes in mortality during the pandemic in Chennai, Tamil Nadu, using data on all-cause mortality within the district. METHODS: For this observational study, we analysed comprehensive death registrations in Chennai, from Jan 1, 2016, to June 30, 2021. We estimated expected mortality without the effects of the COVID-19 pandemic by fitting models to observed mortality time series during the pre-pandemic period, with stratification by age and sex. Additionally, we considered three periods of interest: the first 4 weeks of India's first lockdown (March 24 to April 20, 2020), the 4-month period including the first wave of the pandemic in Chennai (May 1 to Aug 31, 2020), and the 4-month period including the second wave of the pandemic in Chennai (March 1 to June 30, 2021). We computed the difference between observed and expected mortality from March 1, 2020, to June 30, 2021, and compared pandemic-associated mortality across socioeconomically distinct communities (measured with use of 2011 census of India data) with regression analyses. FINDINGS: Between March 1, 2020, and June 30, 2021, 87 870 deaths were registered in areas of Chennai district represented by the 2011 census, exceeding expected deaths by 25 990 (95% uncertainty interval 25 640-26 360) or 5·18 (5·11-5·25) excess deaths per 1000 people. Stratified by age, excess deaths numbered 21·02 (20·54-21·49) excess deaths per 1000 people for individuals aged 60-69 years, 39·74 (38·73-40·69) for those aged 70-79 years, and 96·90 (93·35-100·16) for those aged 80 years or older. Neighbourhoods with lower socioeconomic status had 0·7% to 2·8% increases in pandemic-associated mortality per 1 SD increase in each measure of community disadvantage, due largely to a disproportionate increase in mortality within these neighbourhoods during the second wave. Conversely, differences in excess mortality across communities were not clearly associated with socioeconomic status measures during the first wave. For each increase by 1 SD in measures of community disadvantage, neighbourhoods had 3·6% to 8·6% lower pandemic-associated mortality during the first 4 weeks of India's country-wide lockdown, before widespread SARS-CoV-2 circulation was underway in Chennai. The greatest reductions in mortality during this early lockdown period were observed among men aged 20-29 years, with 58% (54-62) fewer deaths than expected from pre-pandemic trends. INTERPRETATION: Mortality in Chennai increased substantially but heterogeneously during the COVID-19 pandemic, with the greatest burden concentrated in disadvantaged communities. Reported COVID-19 deaths greatly underestimated pandemic-associated mortality. FUNDING: National Institute of General Medical Sciences, Bill & Melinda Gates Foundation, National Science Foundation. TRANSLATION: For the Hindi translation of the abstract see Supplementary Materials section.
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Discrepancies between all-cause and reported COVID-19 mortality in Madurai closely resemble findings in other settings within India, both over time and across demographic strata.
“Discrepancies between all-cause and reported COVID-19 mortality in Madurai closely resemble findings in other settings within India, both over time and across demographic strata3,27,55–58.”
From Attributed causes of excess mortality during the COVID-19 pandemic in a south Indian city (2023) · cites this paper as [57]
All-cause mortality declined during the lockdown period in Madurai, consistent with observations elsewhere in India.
“it is important to note that all-cause mortality declined during this period in Madurai, consistent with observations elsewhere in India57.”
From Attributed causes of excess mortality during the COVID-19 pandemic in a south Indian city (2023) · cites this paper as [57]
The population health impacts of the COVID-19 pandemic are less well understood in low- and middle-income countries, where routine mortality surveillance before the pandemic was patchy.
“These impacts are less well understood in low- and middle-income countries [1–4], where routine mortality surveillance before the pandemic was patchy [5–7].”
From Estimates of pandemic excess mortality in India based on civil registration data (2022) · cites this paper as [4]
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References 32 · Cited by 41
- Authors
- Lewnard, J. A., Mahmud, A., Narayan, T., Wahl, B., Selvavinayagam, T. S., Mohan B, C., & Laxminarayan, R.
- Affiliations
- University of California, Berkeley (US)
- University of Chicago (US)
- Johns Hopkins University (US)
- Government of Tamil Nadu (IN)
- Center for Disease Dynamics, Economics & Policy (US)
- Corresponding author
- Lewnard, Joseph A
- Venue
- The Lancet Infectious Diseases
- Publisher
- Elsevier BV
- Published
- 2022-04
- Volume
- 22
- Issue
- 4
- Pages
- 463-472
- ISSN
- 1473-3099 (ISSN-L)
- PMC
- PMC8694707
- OpenAlex
- W4200226905
- Cited by
- 41
- References
- 32
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 16 · 2023: 10 · 2022: 9
- FWCI
- 3.38
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- The Lancet Infectious Diseases (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- Funders
- Bill and Melinda Gates Foundation (INV029062)
- National Science Foundation (CCF1918628)
- National Institutes of Health
- National Institute of General Medical Sciences (MIDASNI2020\u20133)
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Health Sciences › Medicine › Oncology › COVID-19 and healthcare impacts
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Keywords
- COVID-19 pandemic, excess mortality, all-cause mortality, lockdown, socioeconomic disparities, socioeconomic status, age-specific mortality, older adults, Chennai, Tamil Nadu, COVID-19 waves, 2011 census, 2020 lockdown
- MeSH terms
- COVID-19, SARS-CoV-2, Adult, Aged, Aged, 80 and over, Communicable Disease Control, Humans, India, Male, Middle Aged, Mortality, Young Adult, Pandemics
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