Modeling and forecasting of COVID-19 spreading by delayed stochastic differential equations

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...

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Detalhes bibliográficos
Autor principal: Mahrouf, Marouane (author)
Outros Autores: Boukhouima, Adnane (author), Zine, Houssine (author), Lotfi, El Mehdi (author), Torres, Delfim F. M. (author), Yousfi, Noura (author)
Formato: article
Idioma:eng
Publicado em: 2021
Assuntos:
COVID-19
Coronaviruses
Mathematical modeling
Delayed stochastic differential equations (DSDEs)
Texto completo:http://hdl.handle.net/10773/30582
País:Portugal
Oai:oai:ria.ua.pt:10773/30582
Descrição
Resumo: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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