Method for Active Pandemic Curve Management (MAPCM)

  1. Willem G. Odendaal

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Abstract

The COVID-19 pandemic of 2020 prompted stringent mitigation measures to “flatten the curve” quickly leading to an asphyxiated US economy as a national side effect. There are severe drawbacks to this strategy. The resulting flattened curve remains exponential and always under utilizes available healthcare capacity with a chance of still overburdening it. Moreover, while a mitigation strategy involving isolation and containment can scale down infections, it not only prolongs the outbreak significantly, but also leaves a susceptible population in its wake that’s ripe for a secondary outbreak. Since economic activity is inversely proportional to mitigation, curtailing the outbreak with sustained mitigation can stifle the economy severely with disastrous repercussions. Full mitigation for the duration of an outbreak is therefore unsustainable and, overall, a poor solution with potentially catastrophic consequences that could’ve been avoided. A new strategy, coined a “Method for Active Pandemic Curve Management” , or MAPCM , presented herein can shape the outbreak curve in a controlled manner for optimal utilization of healthcare resources during the pandemic, while drastically shortening the outbreak duration compared to mitigation by itself without trading off lives. This method allows mitigation measures to be relaxed gradually from day one, which enables economic activity to resume gradually from the onset of a pandemic. Since outbreak curves (such as hospitalizations) can be programmed using this method, they can also be shaped to accommodate changing needs during the outbreak; and to build herd immunity without the damaging side effects. The method can also be used to ease out of containment. MAPCM is a method and not a model . It is compatible with any appropriate outbreak model; and herein it is illustrated in examples using a hybrid logistic model.

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    SciScore for 10.1101/2020.04.06.20055699: (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 10.1101/2020.04.06.20055699v2 on medRxiv
  3. Version published to 10.1101/2020.04.06.20055699v1 on medRxiv