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Stochastic persistence and stationary distribution in an SIS epidemic model with media coverage

This paper aims to study an SIS epidemic model with media coverage from a general deterministic model to a stochastic differential equation with environment fluctuation. Mathematically, we use the Markov semigroup theory to prove that the basic reproduction number [Formula: see text] can be used to...

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Detalles Bibliográficos
Autores principales: Guo, Wenjuan, Cai, Yongli, Zhang, Qimin, Wang, Weiming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125861/
https://www.ncbi.nlm.nih.gov/pubmed/32288104
http://dx.doi.org/10.1016/j.physa.2017.11.137
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author Guo, Wenjuan
Cai, Yongli
Zhang, Qimin
Wang, Weiming
author_facet Guo, Wenjuan
Cai, Yongli
Zhang, Qimin
Wang, Weiming
author_sort Guo, Wenjuan
collection PubMed
description This paper aims to study an SIS epidemic model with media coverage from a general deterministic model to a stochastic differential equation with environment fluctuation. Mathematically, we use the Markov semigroup theory to prove that the basic reproduction number [Formula: see text] can be used to control the dynamics of stochastic system. Epidemiologically, we show that environment fluctuation can inhibit the occurrence of the disease, namely, in the case of disease persistence for the deterministic model, the disease still dies out with probability one for the stochastic model. So to a great extent the stochastic perturbation under media coverage affects the outbreak of the disease.
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spelling pubmed-71258612020-04-08 Stochastic persistence and stationary distribution in an SIS epidemic model with media coverage Guo, Wenjuan Cai, Yongli Zhang, Qimin Wang, Weiming Physica A Article This paper aims to study an SIS epidemic model with media coverage from a general deterministic model to a stochastic differential equation with environment fluctuation. Mathematically, we use the Markov semigroup theory to prove that the basic reproduction number [Formula: see text] can be used to control the dynamics of stochastic system. Epidemiologically, we show that environment fluctuation can inhibit the occurrence of the disease, namely, in the case of disease persistence for the deterministic model, the disease still dies out with probability one for the stochastic model. So to a great extent the stochastic perturbation under media coverage affects the outbreak of the disease. Elsevier B.V. 2018-02-15 2017-12-05 /pmc/articles/PMC7125861/ /pubmed/32288104 http://dx.doi.org/10.1016/j.physa.2017.11.137 Text en © 2017 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Guo, Wenjuan
Cai, Yongli
Zhang, Qimin
Wang, Weiming
Stochastic persistence and stationary distribution in an SIS epidemic model with media coverage
title Stochastic persistence and stationary distribution in an SIS epidemic model with media coverage
title_full Stochastic persistence and stationary distribution in an SIS epidemic model with media coverage
title_fullStr Stochastic persistence and stationary distribution in an SIS epidemic model with media coverage
title_full_unstemmed Stochastic persistence and stationary distribution in an SIS epidemic model with media coverage
title_short Stochastic persistence and stationary distribution in an SIS epidemic model with media coverage
title_sort stochastic persistence and stationary distribution in an sis epidemic model with media coverage
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125861/
https://www.ncbi.nlm.nih.gov/pubmed/32288104
http://dx.doi.org/10.1016/j.physa.2017.11.137
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