ON THE UNCERTAINTY ABOUT HERD IMMUNITY LEVELS REQUIRED TO STOP COVID-19 EPIDEMICS

  1. Daniel Gianola

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Abstract

COVID-19 evolved into a pandemic in 2020 affecting more than 150 countries. Given the absence of a vaccine, discussion has taken place on the strategy of allowing the virus to spread in a population, to increase population “herd immunity”. Knowledge of the minimum proportion of a population required to have recovered from COVID-19 infection in order to attain “herd” immunity, P crit , is important for formulating epidemiological policy. A method for measuring uncertainty about P crit based on a widely used package, EpiEstim, is derived. The procedure is illustrated using data from twelve countries at two early times during the COVID-19 epidemic. It is shown that simple plug-in measures of confidence on estimates of P crit are misleading, but that a full characterization of statistical uncertainty can be derived from EpiEstim, which reports percentiles only. Because of the important levels of uncertainty, it is risky to design epidemiological policy based on guidance provided by a single point estimate.

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    SciScore for 10.1101/2020.05.31.20118695: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    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: 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.

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  2. Version published to 10.1101/2020.05.31.20118695 on medRxiv