Japan’s Covid mitigation strategy and its epidemic prediction

This article has been Reviewed by the following groups

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Abstract

The COVID-19 epidemic curve in Japan was constructed based on daily reported data from January 14, 2020 until April 20, 2021. A SEIR compartmental model was used for the curve fitting by updating the estimation per wave. In the current vaccination pace of 1/1000, restrictions (state of emergency in Japan) would be repeated 4 times until the end of next March. In the case of 1/500, another round of restriction would be required in the summer 2021, after which the infection would be mitigated. In the case of 1/250, there would be no need for restriction after the current spring restriction. The scenario of completing the vaccination of 110 million people by the end of March 2020 corresponds to the case of 1/250 in this curve. When considering the likely spread of variant with greater infectiousness (here we assume 1.3 times greater than the original virus), 1/500 pace of vaccination would not be enough to contain it and need several series of restrictions. There are currently several variants of concern that are already spreading in urban areas in this country. In the new stage of the replacement of variants, if the vaccination pace could not be quadrupled from the current pace, Japan could not become a zero covid (zero corona) country at least one year.

Article activity feed

  1. SciScore for 10.1101/2021.05.06.21256476: (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.


    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.