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Meta-analysis of nationwide SARS-CoV-2 infection fatality rates in India

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  • Lauren Zimmermann
  • Bhramar Mukherjee

Abstract

There has been much discussion and debate around underreporting of deaths in India in media articles and in the scientific literature. In this brief report, we aim to meta-analyze the available/inferred estimates of infection fatality rates for SARS-CoV-2 in India based on the existent literature. These estimates account for uncaptured deaths and infections. We consider empirical excess death estimates based on all-cause mortality data as well as disease transmission-based estimates that rely on assumptions regarding infection transmission and ascertainment rates in India. Through an initial systematic review (Zimmermann et al., 2021) that followed PRISMA guidelines and comprised a search of databases PubMed, Embase, Global Index Medicus, as well as BioRxiv, MedRxiv, and SSRN for preprints (accessed through iSearch) on July 3, 2021, we further extended the search verification through May 26, 2022. The screening process yielded 15 studies qualitatively analyzed, of which 9 studies with 11 quantitative estimates were included in the meta-analysis. Using a random effects meta-analysis framework, we obtain a pooled estimate of nationwide infection fatality rate (defined as the ratio of estimated deaths over estimated infections) and a corresponding confidence interval. Death underreporting from excess deaths studies varies by a factor of 6.1–13.0 with nationwide cumulative excess deaths ranging from 2.6–6.3 million, whereas the underreporting from disease transmission-based studies varies by a factor of 3.5–7.3 with SARS-CoV-2 related nationwide estimated total deaths ranging from 1.4–3.4 million, through June 2021 with some estimates extending to 31 December 2021. Underreporting of infections was found previously (Zimmermann et al., 2021) to be 24.9 (relying on the latest 4th nationwide serosurvey from 14 June-6 July 2021 prior to launch of the vaccination program). Conservatively, by considering the lower values of these available estimates, we infer that approximately 95% of infections and 71% of deaths were not accounted for in the reported figures in India. Nationwide pooled infection fatality rate estimate for India is 0.51% (95% confidence interval [CI]: 0.45%– 0.58%). We often tend to compare countries across the world in terms of total reported cases and deaths. Although the US has the highest number of reported cumulative deaths globally, after accounting for underreporting, India appears to have the highest number of cumulative total deaths (reported + unreported). However, the large number of estimated infections in India leads to a lower infection fatality rate estimate than the US, which in part is due to the younger population in India. We emphasize that the age-structure of different countries must be taken into consideration while making such comparisons. More granular data are needed to examine heterogeneities across various demographic groups to identify at-risk and underserved populations with high COVID mortality; the hope is that such disaggregated mortality data will soon be made available for India.

Suggested Citation

  • Lauren Zimmermann & Bhramar Mukherjee, 2022. "Meta-analysis of nationwide SARS-CoV-2 infection fatality rates in India," PLOS Global Public Health, Public Library of Science, vol. 2(9), pages 1-10, September.
  • Handle: RePEc:plo:pgph00:0000897
    DOI: 10.1371/journal.pgph.0000897
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    References listed on IDEAS

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    1. Hazhir Rahmandad & Tse Yang Lim & John Sterman, 2021. "Behavioral dynamics of COVID‐19: estimating underreporting, multiple waves, and adherence fatigue across 92 nations," System Dynamics Review, System Dynamics Society, vol. 37(1), pages 5-31, January.
    2. Lauren Zimmermann & Subarna Bhattacharya & Soumik Purkayastha & Ritoban Kundu & Ritwik Bhaduri & Parikshit Ghosh & Bhramar Mukherjee, 2021. "SARS-CoV-2 Infection Fatality Rates in India: Systematic Review, Meta-analysis and Model-based Estimation," Studies in Microeconomics, , vol. 9(2), pages 137-179, December.
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