Predicting the COVID-19 epidemic in Algeria using the SIR model

  1. Mohamed Samir Boudrioua
  2. Abderrahmane Boudrioua

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Abstract

The aim of this study is to predict the daily infected cases with Coronavirus (COVID-19) in Algeria. We apply the SIR model on data from 25 February 2020 to 24 April 2020 for the prediction. Following Huang et al (12), we develop two SIR models, an optimal model and a model in a worst-case scenario COVID-19. We estimate the parameters of our models by minimizing the negative log likelihood function using the Nelder-Mead method. Based on the simulation of the two models, the epidemic peak of COVID-19 is predicted to attain 24 July 2020 in a worst-case scenario, and the COVID-19 disease is expected to disappear in the period between September 2020 and November 2020 at the latest. We suggest that Algerian authorities need to implement a strict containment strategy over a long period to successfully decrease the epidemic size, as soon as possible.

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  1. Version published to 10.1101/2020.04.25.20079467v7 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.04.25.20079467: (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

    Software and Algorithms
    SentencesResources
    Python software version 3.6.4 was used to implement the SIR model and solve it.
    Python
    suggested: (IPython, RRID:SCR_001658)

    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 10.1101/2020.04.25.20079467v6 on medRxiv
  4. Version published to 10.1101/2020.04.25.20079467v5 on medRxiv
  5. Version published to 10.1101/2020.04.25.20079467v4 on medRxiv
  6. Version published to 10.1101/2020.04.25.20079467v3 on medRxiv
  7. Version published to 10.1101/2020.04.25.20079467v2 on medRxiv
  8. Version published to 10.1101/2020.04.25.20079467v1 on medRxiv