Intrinsic growth rules of patients infected, dead and recovered with 2019 novel coronavirus in mainland China

  1. Chuanliang Han
  2. Yimeng Liu
  3. Saini Yang

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Abstract

An outbreak of a novel coronavirus (SARS-CoV-2)-infected pneumonia (COVID-19) was first diagnosed in Wuhan, China, in December 2019 and then spread rapidly to other regions. We collected the time series data of the cumulative number of confirmed infected, dead, and cured cases from the health commissions in 31 provinces in mainland China. A descriptive model in a logistic form was formulated to infer the intrinsic epidemic rules of COVID-19, which illustrates robustness spatially and temporally. Our model is robust ( R 2 >0.95) to depict the intrinsic growth rule for the cumulative number of confirmed infected, dead, and cured cases in 31 provinces in mainland China. Furthermore, we compared the intrinsic epidemic rules of COVID-19 in Hubei with that of severe acute respiratory syndrome (SARS) in Beijing, which was obtained from the Ministry of Public Health of China in 2003. We found that the infected case is the earliest to be saturated and has the lowest semi-saturation period compared with deaths and cured cases for both COVID-19 and SARS. All the three types of SARS cases are later to saturate and have longer semi-saturation period than that of COVID-19. Despite the virus caused SARS (SARS-CoV) and the virus caused COVID-19 (SARS-CoV-2) are homologous, the duration of the outbreak would be shorter for COVID-19.

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    SciScore for 10.1101/2020.02.23.20024802: (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

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  2. Version published to 10.1101/2020.02.23.20024802 on medRxiv