Forecasting the outbreak of COVID-19 in Lebanon

  1. Omar El Deeb
  2. Maya Jalloul

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Abstract

This note explores the spread of the Coronavirus disease 2019 (COVID-19) in Lebanon using available data until August 25th, 2020 and forecasts the number of infections until the end of September using four diffierent scenarios for mitigation measures reflected in the reproductive number R t . Mitigation measures in Lebanon date back to early March soon after the first confirmed cases, and have been gradually lifted as of May. Thereafter, the country has witnessed a slow yet steady increase in the number of cases that has been significantly exacerbated after the explosion at Beirut harbor on August 4. Furthermore, we estimate the daily active cases in need of intensive care compared to the available number of beds and we assess accordingly that this capacity will be exhausted within a short span of time, unless severe measures are imposed.

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  1. ScreenIT

    SciScore for 10.1101/2020.09.03.20187880: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot 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.

    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 10.1101/2020.09.03.20187880 on medRxiv