Impact of information and Lévy noise on stochastic COVID-19 epidemic model under real statistical data

Autor:	Peijiang Liu, Lifang Huang, Anwarud Din, Xiangxiang Huang
Jazyk:	angličtina
Rok vydání:	2022
Předmět:	Stochastic COVID-19 model Lévy jump information intervention extinction persistence numerical simulation Environmental sciences GE1-350 Biology (General) QH301-705.5
Zdroj:	Journal of Biological Dynamics, Vol 16, Iss 1, Pp 236-253 (2022)
Druh dokumentu:	article
ISSN:	17513758 1751-3766 1751-3758
DOI:	10.1080/17513758.2022.2055172
Popis:	In this paper, we consider the dynamical behaviour of a stochastic coronavirus (COVID-19) susceptible-infected-removed epidemic model with the inclusion of the influence of information intervention and Lévy noise. The existence and uniqueness of the model positive solution are proved. Then, we establish a stochastic threshold as a sufficient condition for the extinction and persistence in mean of the disease. Based on the available COVID-19 data, the parameters of the model were estimated and we fit the model with real statistics. Finally, numerical simulations are presented to support our theoretical results.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/a3141b02bd014f8f9f33decb5b2ee6d7 Zobrazit plný text záznamu View record in DOAJ