Modeling the COVID-19 epidemic in Okinawa

  1. Simone Pigolotti
  2. Davide Chiuchiu
  3. Paula Villa Martin
  4. Deepak Bhat

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Abstract

We analyze current data on the COVID-19 spreading in Okinawa, Japan. We find that the initial spread is characterized by a doubling time of about 5 days. We implement a model to forecast the future spread under different scenarios. The model predicts that, if significant containment measures are not taken, a large fraction of the population will be infected with COVID-19, with the peak of the epidemic expected at the end of May and intensive care units having largely exceeded capacity. We analyzed scenarios implementing strong containment measures, similar to those imposed in Europe. The model predicts that an immediate implementation of strong containment measures (on the 19th of April) will significantly reduce the death count. We assess the negative consequences of these measures being implemented with a delay, or not being sufficiently stringent.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.20.20071977: (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.
    • Thank you for including a protocol registration statement.

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  2. Version published to 10.1101/2020.04.20.20071977v1 on medRxiv