Modeling and Forecasting of COVID-19 Spreading by Delayed Stochastic Differential Equations

Authors:
  • MMMarouane Mahrouf
    Marouane Mahrouf
  • ABAdnane Boukhouima
    Adnane Boukhouima
  • HZHoussine Zine
    Houssine Zine
  • ELEl Mehdi Lotfi
    El Mehdi Lotfi
  • DTDelfim F. M. Torres
    Delfim F. M. Torres
  • NYNoura Yousfi
    Noura Yousfi
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Abstract
The novel coronavirus disease (COVID-19) pneumonia has posed a great threat to the world recent months by causing many deaths and enormous economic damage worldwide. The first case of COVID-19 in Morocco was reported on 2 March 2020, and the number of reported cases has increased day by day. In this work, we extend the well-known SIR compartmental model to deterministic and stochastic time-delayed models in order to predict the epidemiological trend of COVID-19 in Morocco and to assess the potential role of multiple preventive measures and strategies imposed by Moroccan authorities. The main features of the work include the well-posedness of the models and conditions under which the COVID-19 may become extinct or persist in the population. Parameter values have been estimated from real data and numerical simulations are presented for forecasting the COVID-19 spreading as well as verification of theoretical results.
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