Classification of the infection status of COVID-19 in 190 countries

  1. Takashi Odagaki
  2. Reiji Suda

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

We propose a simple method to determine the infection rate from the time dependence of the daily confirmed new cases, in which the logarithm of the rate is fitted by piece-wise quadratic functions. Exploiting this method, we analyze the time dependence of the outbreak of COVID-19 in 190 countries around the world and determine the status of the outbreak in each country by the dependence of the infection rate on the number of new cases. We show that the infection status of each country can be completely classified into nine different states and that the infection status of countries succeeded in controlling COVID-19 implies the importance of the quarantine and/or self-isolation measure.

Article activity feed

  1. Version published to 10.1101/2020.12.17.20248445v2 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.12.17.20248445: (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.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.12.17.20248445v1 on medRxiv