Quantification of the South African Lockdown Regimes, for the SARS-CoV-2 Pandemic, and the Levels of Immunity They Require to Work

  1. S. J. Childs

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Abstract

This research quantifies the various South African lockdown regimes, for the SARS-CoV-2 pandemic, in terms of the basic reproduction number, r 0 . It further calculates the levels of immunity required for these selfsame lockdown regimes to begin to work, then predicts their perceived values, should infections have been underestimated by a factor of 10. The first, level-5 lockdown was a valiant attempt to contain the highly infectious, SARS-CoV-2 virus, based on a limited knowledge. Its basic reproduction number (r 0 = 1.93) never came anywhere close to the requirement of being less than unity. Obviously, it could be anticipated that the same would apply for subsequent, lower levels of lockdown. The basic reproduction number for the level-3 lockdown was found to be 2.34 and that of the level-4 lockdown, 1.69. The suggestion is therefore that the level-4 lockdown might have been marginally ‘smarter’ than the ‘harder’, level-5 lockdown, although its basic reproduction number may merely reflect an adjustment by the public to the new normal, or the ever-present error associated with data sets, in general. The pandemic’s basic reproduction number was calculated to be 3.16, in the Swedish context. The lockdowns therefore served to ensure that the medical system was not overwhelmed, bought it valuable time to prepare and provided useful data. The lockdowns nonetheless failed significantly in meeting any objective to curtail the pandemic.

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  1. ScreenIT

    SciScore for 10.1101/2020.07.11.20151555: (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.

    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.

  2. Version published to 10.1101/2020.07.11.20151555v1 on medRxiv