Modeling the emergence of vaccine-resistant variants with Gaussian convolution COVID-19: Could the wrong strategy ruin vaccine efficiency?

  1. Christian Bongiorno
  2. John Cagnol

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Abstract

The SARS-CoV-2 virus, which is responsible for the COVID-19 pandemic, has been shown to mutate. In the absence of a vaccine, natural selection will favor variants with higher transmissibility rates. However, when a substantial portion of the population is vaccinated, natural selection will shift towards favoring variants that can resist the vaccine. These variants can therefore become dominant and even cancel out the benefit of the vaccine. This paper develops a compartmental model which simulates this phenomenon and shows how various vaccination strategies can lead to the emergence of vaccine-resistant variants.

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    SciScore for 10.1101/2021.07.07.21259916: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your code.

    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.

    Results from scite Reference Check: We found no unreliable references.

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  2. Version published to 10.1101/2021.07.07.21259916v1 on medRxiv