Prediction of the Epidemic Peak of Covid19 in Egypt, 2020

  1. Eman D. El Desouky

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Objectives

Since December 2019 a pandemic of new novel coronavirus has started from Wuhan, China, in Egypt, the first case reported on February 14, 2020. In this study we aimed to predict the time of possible peak and simulate the changes could be happen by the social behavior of Egyptians during Ramadan (the holy month).

Methods

SIR and SEIR compartmental models were used to predict the peak time. We simulated different expected scenarios based to examine their effects on the peak timing.

Results

We found that the peak most likely to be in middle of June 2020. Simulating different transmission rate probability and R0 the earliest peak could to be in the May 20 and latest one could be in 18 July. The peak shifted much earlier to 11 th April 2020 without lockdown and other mitigation strategies.

Conclusion

Social behaviors of citizens during the holy month will dramatically affect the peak timing. Mitigations strategies and other lockdown measure helped to delay the expected peak.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.04.30.20086751: (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: Thank you for sharing your code and data.

    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.

    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.

  2. Version published to 10.1101/2020.04.30.20086751v1 on medRxiv