Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/30582
Title: Modeling and forecasting of COVID-19 spreading by delayed stochastic differential equations
Author: Mahrouf, Marouane
Boukhouima, Adnane
Zine, Houssine
Lotfi, El Mehdi
Torres, Delfim F. M.
Yousfi, Noura
Keywords: COVID-19
Coronaviruses
Mathematical modeling
Delayed stochastic differential equations (DSDEs)
Issue Date: Mar-2021
Publisher: MDPI
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.
Peer review: yes
URI: http://hdl.handle.net/10773/30582
DOI: 10.3390/axioms10010018
ISSN: 2075-1680
Appears in Collections:CIDMA - Artigos
DMat - Artigos
SCG - Artigos

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