1-C Nonlinear Covid-19 Epidemic Model and Application to the Epidemic Prediction in France

  1. J.-P. Quadrat

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Abstract

We have shown in a previous paper that the standard time-invariant SIR model was not effective to predict the 2019-20 coronavirus pandemic propagation. We have proposed a new model predicting z the logarithm of the number of detected-contaminated people. It follows a linear dynamical system ż = b − az . We show here that we can improve this prediction using a non linear model ż = b − az r where r is an exponent that we have also to estimate from data. Some countries have an epidemic with a bell shaped form that we call unimodal epidemic. With this new model, we fit observed data of different countries having an unimodal epidemic with a surprising quality. We discuss also the prediction quality obtained with these models at the epidemic start in France. Finally, we evaluate the containment impact on the Covid French mortality in hospitals.

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    SciScore for 10.1101/2020.05.24.20111807: (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 10.1101/2020.05.24.20111807v1 on medRxiv