On the Stochastic Modeling of COVID-19 under the Environmental White Noise

Autor: Shah Hussain, Elissa Nadia Madi, Hasib Khan, Haseena Gulzar, Sina Etemad, Shahram Rezapour, Mohammed K. A. Kaabar
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Journal of Function Spaces, Vol 2022 (2022)
Druh dokumentu: article
ISSN: 2314-8888
DOI: 10.1155/2022/4320865
Popis: The COVID-19 pandemic has caused emotional loss to people around the world and provides an unusual test for public welfare, educational framework, food frameworks, and the world of work. The economic and social turmoil caused by this epidemic is increasing, and many people are at risk of falling into oppressive poverty. In this article, we describe the pandemic of infectious illness with the help of stochastic mathematical modeling. Based on the environmental white noise and by building appropriate Lyapunov functions and by applying Ito’s formula, a few subjective properties are gotten. We provide a new mathematical model for the COVID-19 spread. The novel stochastic model is used to analyze the existence and prevalence of the disease, as well as its extinction. A numerical approach is developed for computing approximate solutions of the model. We show numerical simulations of deterministic and stochastic models of COVID-19 by utilizing the MATLAB software. In this direction, three graphs are included in the paper for the numerical interpretation of the stochastic model with the help of existing parametric and initial values for the model.
Databáze: Directory of Open Access Journals
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