paper

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

arXiv:2102.04260 · doi:10.3390/axioms10010018

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.

This is a preprint of a paper whose final and definite form is published, open access, by 'Axioms' (ISSN: 2075-1680). Submitted Axioms: 2 Dec 2020; Revised: 20 and 31 Jan 2021; correction to proofs: 4 Feb 2021

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