Evolution of COVID-19 pandemic: Power-law growth and saturation

  1. Soumyadeep Chatterjee
  2. Ali Asad
  3. B. Shayak
  4. Shashwat Bhattacharya
  5. Shadab Alam
  6. Mahendra K. Verma

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Abstract

In this paper, we analyze the real-time infection data of COVID-19 epidemic for 21 nations up to June 30, 2020. For most of these nations, the total number of infected individuals exhibits a succession of exponential growth and power-law growth before the flattening of the curve. In particular, we find a universal growth before they reach saturation. However, at present, India, which has I ( t ) ~ t 2 , and Russia and Brazil, which have I ( t ) ~ t , are yet to flatten their curves. Thus, the polynomials of the I ( t ) curves provide valuable information on the stage of the epidemic evolution, thus on the life cycle of COVID-19 pandemic. Besides these detailed analyses, we compare the predictions of an extended SEIR model and a delay differential equation-based model with the reported infection data and observed good agreement among them, including the behaviour. We argue that the power laws in the epidemic curves may be due to lockdowns.

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  1. Version published to 10.1101/2020.05.05.20091389v3 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.05.05.20091389: (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.

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  3. Version published to 10.1101/2020.05.05.20091389v2 on medRxiv
  4. Version published to 10.1101/2020.05.05.20091389v1 on medRxiv