Evolution of the COVID Pandemic: A Technique for Mathematical Analysis of Data

  1. K. Tennakone
  2. L. Ajith DeSilva
  3. K. J. Wimalasena
  4. Z. J. Welchel

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Abstract

The analysis of COVID-19 statistics in different regions of the world with the intention of understanding the trend of progression of the pandemic is a task of paramount importance. Publicly available data includes cumulative number of cases, new cases each day, and the mortality. Extracting information from this data necessitates mathematical modeling. In this note a simple technique is adopted to determine the trend towards stabilized elimination of the infection, as implicated by saturation of the cumulative number of cases. Results pertaining to several representative regions of the world are presented. In several regions, evidence there to the effect that the pandemic will come to an end. The estimated saturation values of the cumulative numbers are indicated.

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    SciScore for 10.1101/2020.05.08.20095273: (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.

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    • No protocol registration statement was detected.

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  2. Version published to 10.1101/2020.05.08.20095273v2 on medRxiv
  3. Version published to 10.1101/2020.05.08.20095273v1 on medRxiv