Estimating COVID-19 under-reporting across 86 nations: implications for projections and control

  1. Hazhir Rahmandad
  2. Tse Yang Lim
  3. John Sterman

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

COVID-19 prevalence and mortality remain uncertain. For all 86 countries with reliable testing data we estimate how asymptomatic transmission, disease acuity, hospitalization, and behavioral responses to risk shape pandemic dynamics. Estimated cumulative cases and deaths through 10 July 2020 are 10.5 and 1.47 times official reports, yielding an infection fatality rate (IFR) of 0.65%, with wide variation across nations. Despite underestimation, herd immunity remains distant. Sufficient early testing could have averted 39.7 (35.3-45.3) million cases and 218 (191-257) thousand deaths. Responses to perceived risk cause the reproduction number to settle near 1, but with very different steady-state incidence, while some nations experience endogenous rebounds. Scenarios through March 2021 show modest enhancements in responsiveness could reduce cumulative cases ≈80%, to 271 (254-412) million across these nations.

One Sentence Summary

COVID-19 under-reporting is large, varies widely across nations, and strongly conditions projected outbreak dynamics.

Article activity feed

  1. Version published to 10.1101/2020.06.24.20139451v4 on medRxiv
  2. Version published to 10.1101/2020.06.24.20139451v3 on medRxiv
  3. Version published to 10.1101/2020.06.24.20139451v2 on medRxiv
  4. ScreenIT

    SciScore for 10.1101/2020.06.24.20139451: (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: Thank you for sharing your code and data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  5. Version published to 10.1101/2020.06.24.20139451v1 on medRxiv