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

• Autor(a) principal: Mahrouf, Marouane
• Data de Publicação: 2021
• Outros Autores: Boukhouima, Adnane, Zine, Houssine, Lotfi, El Mehdi, Torres, Delfim F. M., Yousfi, Noura
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/30582
• topic: COVID-19; Coronaviruses; Mathematical modeling; Delayed stochastic differential equations (DSDEs)

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.