Gaussian Statistics and Data-Assimilated Model of Mortality due to COVID-19: China, USA, Italy, Spain, UK, Iran, and the World Total

  1. T.-W. Lee
  2. J.E. Park
  3. David Hung

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Abstract

Covid-19 is characterized by rapid transmission and severe symptoms, leading to deaths in some cases (ranging from 1.5 to 12% of the affected, depending on the country). We identify the Gaussian nature of mortality due to covid-19, as shown in China where it appears to have run its course (during the first sweep of the pandemic at least) and other coutnries, and also in Imperial College modeling. Gaussian distribution involves three parameters, the height, peak location and the width, and the streaming data can be used to infer function value, slope and inflection location as a minimum set of constraints to estimate the subsequent trajectories. Thus, we apply the Gaussian function template as the basis for a data-assimilated model of covid-19 trajectories, first to USA, United Kingdom (UK), Iran and the world total in this study. As more data become available, the Gaussian trajectories are updated, for other nations and also for state-by-state projections in USA.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.06.20055640: (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.
    • Thank you for including a protocol registration statement.

    About SciScore

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  2. Version published to 10.1101/2020.04.06.20055640v1 on medRxiv