Modelling the positive testing rate of COVID-19 in South Africa Using A Semi-Parametric Smoother for Binomial Data

  1. Olajumoke Evangelina Owokotomo
  2. Samuel Manda
  3. Adetayo Kasim
  4. Jurgen Claesen
  5. Ziv Shkedy
  6. Tarylee Reddy

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Abstract

The current outbreak of COVID-19 is a major pandemic that has shaken up the entire world in a short time. South Africa has the highest number of COVID-19 cases in Africa and understanding the country’s disease trajectory is important for government policy makers to plan the optimal COVID-19 intervention strategy. The number of cases is highly correlated with the number of COVID-19 tests undertaking. Thus, current methods of understanding the COVID-19 transmission process in the country based only on the number of cases can be misleading. In light of this, we propose to estimate both the probability of positive cases per tests conducted (the positive testing rate) and the rate in which the positive testing rate changes over time (its derivative) using a flexible semi-parametric model.

We applied the method to the observed positive testing rate in South Africa with data obtained from March 5th to September 2nd 2020. We found that the positive testing rate was declining from early March when the disease was first observed until early May where it kept on increasing. In the month of July 2020, the infection reached its peak then its started to decrease again indicating that the intervention strategy is effective. From mid August, 2020, the rate of change of the positive testing rate indicates that decline in the positive testing rate is slowing down, suggesting that a less effective intervention is currently implemented.

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    SciScore for 10.1101/2020.11.11.20230250: (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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  2. Version published to 10.1101/2020.11.11.20230250v1 on medRxiv