COVID-19 pandemic: A Hill type mathematical model predicts the US death number and the reopening date

  1. Yasser Aboelkassem

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Abstract

A mathematical model that can be used to estimate the total number of cases and deaths due to COVID-19 pandemic is presented in this study. The parameters and the associated uncertainty in the model are optimized and quantified using various reported data sets reported from different countries. The results suggest that, by the mid of June or early July 2020, the outbreak will strongly decay and the US will have about 800K confirmed cases and less than 50K deaths.

This study presents a mathematical model that can be used to estimate the total number of cases and deaths in the US due to COVID-19. The model forecasting about < 800 K cases and < 50 K total numbers of deaths in the United States. The results suggest that late May or early June, 2020 is probably a good time to end the shutdown order and reopen the country for the daily routine business.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.12.20062893: (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

    Software and Algorithms
    SentencesResources
    We have used a Matlab function lsqnonlin to find a set of model parameters which minimize RMS.
    Matlab
    suggested: (MATLAB, RRID:SCR_001622)

    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

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  2. Version published to 10.1101/2020.04.12.20062893v1 on medRxiv