COVID-19: How to Relax Social Distancing If You Must

  1. Daniel Duque
  2. David Paul Morton
  3. Bismark Singh
  4. Zhanwei Du
  5. Remy Pasco
  6. Lauren Ancel Meyers

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Abstract

Following the April 16, 2020 release of the Opening Up America Again guidelines for relaxing COVID-19 social distancing policies, local leaders are concerned about future pandemic waves and lack robust strategies for tracking and suppressing transmission. Here, we present a framework for monitoring COVID-19 hospitalization data to project risks and trigger shelter-in-place orders to prevent overwhelming healthcare surges while minimizing the duration of costly lockdowns. Assuming the relaxation of social distancing increases the risk of infection ten-fold, the optimal strategy for Austin, Texas--the fastest-growing large city in the US--will trigger a total of 135 [90% prediction interval: 126-141] days of sheltering, allow schools to open in the fall, and result in an expected 2929 deaths [90% prediction interval: 2837-3026] by September 2021, which is 29% the annual mortality rate. In the months ahead, policy makers are likely to face difficult choices and the extent of public restraint and cocooning of vulnerable populations may save or cost thousands of lives.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.29.20085134: (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 10.1101/2020.04.29.20085134v1 on medRxiv