A New Compartment Model of COVID-19 Transmission: The Broken-Link Model

  1. Yoichi Ikeda
  2. Kenji Sasaki
  3. Takashi Nakano

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Abstract

We propose a new compartment model of COVID-19 spread, the broken-link model, which includes the effect from unconnected infectious links of the transmission. The traditional SIR-type epidemic models are widely used to analyze the spread status, and the models show the exponential growth of the number of infected people. However, even in the early stage of the spread, it is proven by the actual data that the exponential growth did not occur all over the world. We presume this is caused by the suppression of secondary and higher-order transmissions of COVID-19. We find that the proposed broken-link model quantitatively describes the mechanism of this suppression, which leads to the shape of epicurves of confirmed cases are governed by the probability of unconnected infectious links, and the magnitudes of the cases are proportional to expR0 in each infectious surge generated by a virus of the basic reproduction number R0, and is consistent with the actual data.

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  1. Version published to 10.3390/ijerph19116864
  2. ScreenIT

    SciScore for 10.1101/2022.03.04.22271940: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    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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  3. Version published to 10.1101/2022.03.04.22271940 on medRxiv