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Bayesian forecast of the basic reproduction number during the Covid-19 epidemic in Morocco and Italy

Author

Listed:
  • Mohamed El Fatini
  • Mohamed El Khalifi
  • Richard Gerlach
  • Roger Pettersson

Abstract

In a Covid-19 susceptible-infected-recovered-dead model with time-varying rates of transmission, recovery, and death, the parameters are constant in small time intervals. A posteriori parameters result from the Euler-Maruyama approximation for stochastic differential equations and from Bayes’ theorem. Parameter estimates and 10-day predictions are performed based on Moroccan and Italian Covid-19 data. Mean absolute errors and mean square errors indicate that predictions are of good quality.

Suggested Citation

  • Mohamed El Fatini & Mohamed El Khalifi & Richard Gerlach & Roger Pettersson, 2021. "Bayesian forecast of the basic reproduction number during the Covid-19 epidemic in Morocco and Italy," Mathematical Population Studies, Taylor & Francis Journals, vol. 28(4), pages 228-242, October.
    • Handle: RePEc:taf:mpopst:v:28:y:2021:i:4:p:228-242
    DOI: 10.1080/08898480.2021.1941661
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    Cited by:

    1. Alois Pichler & Dana Uhlig, 2023. "Mortality in Germany during the COVID-19 Pandemic," IJERPH, MDPI, vol. 20(20), pages 1-11, October.
    2. Hani Amir Aouissi & Ahmed Hamimes & Mostefa Ababsa & Lavinia Bianco & Christian Napoli & Feriel Kheira Kebaili & Andrey E. Krauklis & Hafid Bouzekri & Kuldeep Dhama, 2022. "Bayesian Modeling of COVID-19 to Classify the Infection and Death Rates in a Specific Duration: The Case of Algerian Provinces," IJERPH, MDPI, vol. 19(15), pages 1-18, August.

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