A New Adaptive Logistic Model for Epidemics and the Resurgence of COVID-19 in the United States

  1. David H. Roberts

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Abstract

The Adaptive Logistic Model (ALM) of epidemics incorporates the results of infection mitigation effects on the course of an epidemic, and well describes the histories of the COVID-19 epidemics in many countries, including the United States. In particular, it is much more successful than is a basic logistic model. However, in the U.S. these mitigation efforts have recently been relaxed in many places, resulting in the second peak in infections that started in late May of 2020. In this paper the ALM is modified to account for the relaxation of these mitigation effects, leading to the Adaptive Logistic Model 2 (ALM-2). The ALM-2 is then used to understand quantitatively the second peak of COVID-19 cases. The ALM-2 is also successfully applied to the data on deaths even though they do not yet show a second peak.

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  1. ScreenIT

    SciScore for 10.1101/2020.07.17.20156109: (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 10.1101/2020.07.17.20156109v1 on medRxiv