Evidence map›Paper›PMID 36962753›Full record

ArticlePLOS global public health2022

Estimates of pandemic excess mortality in India based on civil registration data.

Murad Banaji, Aashish Gupta

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Article in PLOS global public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

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20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

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  20. Systematic Review of Excess Mortality in India during the Covid-19 Pandemic with Differentiation between Model-Based and Data-Based Mortality Estimates.Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine
    Review
4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Murad BanajiDepartment of Mathematics, Middlesex University London, London, United Kingdom.
Aashish GuptaHarvard Centre for Population and Development Studies, Harvard University, Cambridge, Massachusetts, United States of America.ORCID https://orcid.org/0000-0002-1522-1119

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The population health impacts of the COVID-19 pandemic are less well understood in low and middle-income countries, where mortality surveillance before the pandemic was patchy. Interpreting the limited all-cause mortality data available in India is challenging. We use existing data on all-cause mortality from civil registration systems of twelve Indian states comprising around 60% of the national population to understand the scale and timing of excess deaths in India during the COVID-19 pandemic. We carefully characterize the reasons why registration is incomplete and estimate the extent of coverage in the data. Comparing the pandemic period to 2019, we estimate excess mortality in twelve Indian states, and extrapolate our estimates to the rest of India. We explore sensitivity of the estimates to various assumptions. For the 12 states with available all-cause mortality data, we document an increase of 28% in deaths during April 2020-May 2021 relative to expectations from 2019. This level of increase in mortality, if it applies nationally, would imply 2.8-2.9 million excess deaths. More limited data from June 2021 increases national estimates of excess deaths during April 2020-June 2021 to 3.8 million. With more optimistic or pessimistic assumptions, excess deaths during this period could credibly lie between 2.8 million and 5.2 million. The scale of estimated excess deaths is broadly consistent with expectations based on seroprevalence and COVID-19 fatality rates observed internationally. Moreover, the timing of excess deaths and recorded COVID-19 deaths is similar-they rise and fall at the same time. The surveillance of pandemic mortality in India has been extremely poor, with 8-10 times as many excess deaths as officially recorded COVID-19 deaths. India is among the countries most severely impacted by the pandemic. Our approach highlights the utility of all-cause mortality data, as well as the significant challenges in interpreting it.

Identifiers

PMID36962753
PMCPMC10021303

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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.