Calibrating an SIR model for South Korea COVID-19 infections and predicting vaccination impact

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Abstract

In the span of 1.5 years, COVID-19 has caused more than 4 million deaths worldwide. To prevent such a catastrophe from reoccurring, it is necessary to test and refine current epidemiological models that impact policy decisions. Thus, we developed a deterministic SIR model to examine the long-term transmission dynamics of COVID-19 in South Korea. Using this model, we analyzed how vaccines would affect the number of cases. We found that a 70% vaccination coverage with a 100% effective vaccine would effectively eliminate the number of cases and herd immunity would have been obtained approximately 85 days after February 15 had there not been a reintroduction of cases.

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  1. SciScore for 10.1101/2021.09.27.21264172: (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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