Publication

How to interpret the total number of SARS-CoV-2 infections

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Last modified
  • 05/21/2025
Type of Material
Authors
    Kayoko Shioda, Emory UniversityBenjamin Lopman, Emory University
Language
  • English
Date
  • 2022-06-25
Publisher
  • ELSEVIER SCIENCE INC
Publication Version
Copyright Statement
  • © 2022 Elsevier Ltd. All rights reserved.
Final Published Version (URL)
Title of Journal or Parent Work
Volume
  • 399
Issue
  • 10344
Start Page
  • 2326
End Page
  • 2327
Abstract
  • Counts of reported cases have been the key metric to monitor the COVID-19 pandemic. However, since the beginning, it has been clear that reported cases represent only a fraction of all SARS-CoV-2 infections.1 In The Lancet, COVID-19 Cumulative Infection Collaborators, writing on behalf of the Institute for Health Metrics and Evaluation, report a comprehensive set of global and location-specific estimates of daily and cumulative SARS-CoV-2 infections and the proportion of the population infected for 190 countries and territories up to Nov 14, 2021.2 For this, the authors used a novel approach, combining data from reported cases and deaths, excess deaths attributable to COVID-19, hospitalisations, and seroprevalence surveys to produce more robust estimates in an attempt to minimise biases. According to COVID-19 Cumulative Infection Collaborators findings, a staggering number of people, 3·39 billion (95% uncertainty interval 3·08–3·63) or 43·9% (39·9–46·9) of the global population, are estimated to have been infected one or more times between March, 2020, and November, 2021. Remarkably, this was before the highly transmissible omicron (B.1.1.529) variant swept the globe. These estimates of total infections are wildly different from the number of reported cases, which stood at 254 million as of Nov 14, 2021.3
Author Notes
  • Ben Lopman, Department of Epidemiology and Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA. Email: blopman@emory.edu
Keywords
Research Categories
  • Health Sciences, Public Health
  • Health Sciences, Epidemiology

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