Evidence map›Paper›PMID 34953536›Full record

Observational studyThe Lancet. Infectious diseases2022

All-cause mortality during the COVID-19 pandemic in Chennai, India: an observational study.

Joseph A Lewnard, Ayesha Mahmud, Tejas Narayan, Brian Wahl, T S Selvavinayagam, Chandra Mohan B, Ramanan Laxminarayan

Abstract readObservational Study
In one paragraph

Observational study in The Lancet. Infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Joseph A LewnardDivision of Epidemiology and Division of Infectious Diseases & Vaccinology, School of Public Health, and Center for Computational Biology, College of Engineering, University of California, Berkeley, CA, USA. Electronic address: jlewnard@berkeley.edu.
Ayesha MahmudDepartment of Demography, University of California, Berkeley, CA, USA.
Tejas NarayanCollege of Arts and Sciences, University of Chicago, Chicago, IL, USA.
Brian WahlDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; International Vaccine Access Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
T S SelvavinayagamGovernment of Tamil Nadu, Chennai, Tamil Nadu, India.
Chandra Mohan BGovernment of Tamil Nadu, Chennai, Tamil Nadu, India.
Ramanan LaxminarayanDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Center for Disease Dynamics, Economics & Policy, New Delhi, India; High Meadows Environmental Institute, Princeton University, Princeton, NJ, USA.

Funding

Dev-Core-001P2CHD073964 · NICHD · UNIVERSITY OF CALIFORNIA BERKELEY · PI JOSHUA R. GOLDSTEIN · 2019 to 2026
$2.9M
NICHD NIH HHS P2C HD073964
6 · The paper itself

Abstract

backgroundIndia 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.

methodsFor 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.

findingsBetween 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.

interpretationMortality 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.

fundingNational Institute of General Medical Sciences, Bill & Melinda Gates Foundation, National Science Foundation. TRANSLATION: For the Hindi translation of the abstract see Supplementary Materials section.

Indexed as

COVID-19PandemicsAdultAgedAged, 80 and overCommunicable Disease ControlHumansIndiaMaleMiddle AgedMortalitySARS-CoV-2Young Adult

Identifiers

PMID34953536
PMCPMC8694707

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.