A Phenomenological Analysis of COVID-19

  1. A. O. Macchiavelli
  2. G. V. Martí
  3. J. G. Martí

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Abstract

A phenomenological analysis of the time evolution of some COVID-19 data in terms of a Fermi-Dirac function is presented. In spite of its simplicity, the approach appears to describe the data well and allows to correlate the information in a universal plot in terms of non-dimensional or reduced variables N r = N ( t ) /N max , and t r = t/ Δ T , with N ( t ) being the total number of cases as a function of time, N max the number of total infected cases, and Δ T the diffuseness of the Fermi/Dirac function associated with the rate of infection. The analysis of the reported data for the first outbreak in some selected countries and the results are presented and discussed. The approach is also applicable to subsequent waves. Support of our framework is provided by the SIS limit of the SIR model, and simulations carried out with the SEICRD extension.

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    SciScore for 10.1101/2021.05.23.21249471: (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: 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.

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

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  2. Version published to 10.1101/2021.05.23.21249471v1 on medRxiv