Modelling the Transmission Dynamics of COVID‐19 in Six High‐Burden Countries

  1. Azizur Rahman
  2. Md Abdul Kuddus

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Abstract

The new Coronavirus Disease 19, officially known as COVID‐19, originated in China in 2019 and has since spread worldwide. We presented an age‐structured Susceptible‐Latent‐Mild‐Critical‐Removed (SLMCR) compartmental model of COVID‐19 disease transmission with nonlinear incidence during the pandemic period. We provided the model calibration to estimate parameters with day‐wise COVID‐19 data, i.e., reported cases by worldometer from 15 th February to 30 th March 2020 in six high‐burden countries, including Australia, Italy, Spain, the USA, the UK, and Canada. We estimate transmission rates for each country and found that the country with the highest transmission rate is Spain, which may increase the new cases and deaths than the other countries. We found that saturation infection negatively impacted the dynamics of COVID‐19 cases in all the six high‐burden countries. The study used a sensitivity analysis to identify the most critical parameters through the partial rank correlation coefficient method. We found that the transmission rate of COVID‐19 had the most significant influence on prevalence. The prediction of new cases in COVID‐19 until 30 th April 2020 using the developed model was also provided with recommendations to control strategies of COVID‐19. We also found that adults are more susceptible to infection than both children and older people in all six countries. However, in Italy, Spain, the UK, and Canada, older people show more susceptibility to infection than children, opposite to the case in Australia and the USA. The information generated from this study would be helpful to the decision‐makers of various organisations across the world, including the Ministry of Health in Australia, Italy, Spain, the USA, the UK, and Canada, to control COVID‐19.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.22.20075192: (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: Thank you for sharing your data.

    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 10.1155/2021/5089184
  3. Version published to 10.1101/2020.04.22.20075192v1 on medRxiv