Estimating the probability of New Zealand regions being free from COVID-19 using a stochastic SEIR model

  1. Rafal Bogacz

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Abstract

This report describes a method for estimating the probability that there are no infected or pre-symptomatic individuals in a populations on a basis of historical data describing the number of cases in consecutive days. The method involves fitting a stochastic version of Susceptible Exposed Infected Recovered model, and using the model to calculate the probability that the number of both exposed and infected individuals is equal to 0. The model is used to predict the current probabilities for all District Health Boards in New Zealand. These probabilities are highly correlated with the number of days with no new cases of COVID-19.

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    SciScore for 10.1101/2020.04.20.20073304: (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.

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  2. Version published to 10.1101/2020.04.20.20073304v1 on medRxiv