All-cause excess mortality across 90 municipalities in Gujarat, India, during the COVID-19 pandemic (March 2020-April 2021)

  1. Rolando J. Acosta
  2. Biraj Patnaik
  3. Caroline Buckee
  4. Mathew V. Kiang
  5. Rafael A. Irizarry
  6. Satchit Balsari
  7. Ayesha Mahmud

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Abstract

Official COVID-19 mortality statistics are strongly influenced by local diagnostic capacity, strength of the healthcare and vital registration systems, and death certification criteria and capacity, often resulting in significant undercounting of COVID-19 attributable deaths. Excess mortality, which is defined as the increase in observed death counts compared to a baseline expectation, provides an alternate measure of the mortality shock—both direct and indirect—of the COVID-19 pandemic. Here, we use data from civil death registers from a convenience sample of 90 (of 162) municipalities across the state of Gujarat, India, to estimate the impact of the COVID-19 pandemic on all-cause mortality. Using a model fit to weekly data from January 2019 to February 2020, we estimated excess mortality over the course of the pandemic from March 2020 to April 2021. During this period, the official government data reported 10,098 deaths attributable to COVID-19 for the entire state of Gujarat. We estimated 21,300 [95% CI: 20, 700, 22, 000] excess deaths across these 90 municipalities in this period, representing a 44% [95% CI: 43%, 45%] increase over the expected baseline. The sharpest increase in deaths in our sample was observed in late April 2021, with an estimated 678% [95% CI: 649%, 707%] increase in mortality from expected counts. The 40 to 65 age group experienced the highest increase in mortality relative to the other age groups. We found substantial increases in mortality for males and females. Our excess mortality estimate for these 90 municipalities, representing approximately at least 8% of the population, based on the 2011 census, exceeds the official COVID-19 death count for the entire state of Gujarat, even before the delta wave of the pandemic in India peaked in May 2021. Prior studies have concluded that true pandemic-related mortality in India greatly exceeds official counts. This study, using data directly from the first point of official death registration data recording, provides incontrovertible evidence of the high excess mortality in Gujarat from March 2020 to April 2021.

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  1. Version published to 10.1371/journal.pgph.0000824
  2. ScreenIT

    SciScore for 10.1101/2021.08.22.21262432: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our study has several limitations. First, the data only represent around 5% of the population of Gujarat covering 54 of 162 municipalities[22]. These are urban municipalities. With the exception of Gandhinagar, they do not include data from the municipal corporations of other large urban centers, as these data were unavailable. They also do not include data from the rural gram panchayats. Though the municipalities were spread across the state (see Supplement 1) they represent a convenience sample rather than a random sample, and we are unable to extrapolate our results to estimate deaths across the entire state. Given the high percentage of deaths recorded in the registers, per the NFHS, these data are, however, highly representative of mortality in the municipalities examined. The strikingly high mortality is also consistent with media reports and lived experience and likely representative of the general trend across the state. Second, since we had no data on the yearly population size for each municipality we were unable to calculate mortality rates and make comparisons across municipalities. For the same reason, we were unable to assess excess mortality by demographic indicators. The last published census data are from 2011. While data from electoral rolls are more recent, they do not map to the same geospatial unit of the municipality, and cannot be easily used. We therefore make the assumption that the population remained unchanged between January 2019 and April 2021. Ou...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

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  3. Version published to 10.1101/2021.08.22.21262432 on medRxiv