Dynamics of COVID-19 mathematical model with stochastic perturbation

Acknowledging many effects on humans, which are ignored in deterministic models for COVID-19, in this paper, we consider stochastic mathematical model for COVID-19. Firstly, the formulation of a stochastic susceptible–infected–recovered model is presented. Secondly, we devote with full strength our...

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Autores principales: Zhang, Zizhen, Zeb, Anwar, Hussain, Sultan, Alzahrani, Ebraheem
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2020
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7453696/
https://www.ncbi.nlm.nih.gov/pubmed/32874186
http://dx.doi.org/10.1186/s13662-020-02909-1
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author Zhang, Zizhen
Zeb, Anwar
Hussain, Sultan
Alzahrani, Ebraheem
author_facet Zhang, Zizhen
Zeb, Anwar
Hussain, Sultan
Alzahrani, Ebraheem
author_sort Zhang, Zizhen
collection PubMed
description Acknowledging many effects on humans, which are ignored in deterministic models for COVID-19, in this paper, we consider stochastic mathematical model for COVID-19. Firstly, the formulation of a stochastic susceptible–infected–recovered model is presented. Secondly, we devote with full strength our concentrated attention to sufficient conditions for extinction and persistence. Thirdly, we examine the threshold of the proposed stochastic COVID-19 model, when noise is small or large. Finally, we show the numerical simulations graphically using MATLAB.
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spelling pubmed-74536962020-08-28 Dynamics of COVID-19 mathematical model with stochastic perturbation Zhang, Zizhen Zeb, Anwar Hussain, Sultan Alzahrani, Ebraheem Adv Differ Equ Research Acknowledging many effects on humans, which are ignored in deterministic models for COVID-19, in this paper, we consider stochastic mathematical model for COVID-19. Firstly, the formulation of a stochastic susceptible–infected–recovered model is presented. Secondly, we devote with full strength our concentrated attention to sufficient conditions for extinction and persistence. Thirdly, we examine the threshold of the proposed stochastic COVID-19 model, when noise is small or large. Finally, we show the numerical simulations graphically using MATLAB. Springer International Publishing 2020-08-28 2020 /pmc/articles/PMC7453696/ /pubmed/32874186 http://dx.doi.org/10.1186/s13662-020-02909-1 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Research
Zhang, Zizhen
Zeb, Anwar
Hussain, Sultan
Alzahrani, Ebraheem
Dynamics of COVID-19 mathematical model with stochastic perturbation
title Dynamics of COVID-19 mathematical model with stochastic perturbation
title_full Dynamics of COVID-19 mathematical model with stochastic perturbation
title_fullStr Dynamics of COVID-19 mathematical model with stochastic perturbation
title_full_unstemmed Dynamics of COVID-19 mathematical model with stochastic perturbation
title_short Dynamics of COVID-19 mathematical model with stochastic perturbation
title_sort dynamics of covid-19 mathematical model with stochastic perturbation
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7453696/
https://www.ncbi.nlm.nih.gov/pubmed/32874186
http://dx.doi.org/10.1186/s13662-020-02909-1
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AT hussainsultan dynamicsofcovid19mathematicalmodelwithstochasticperturbation
AT alzahraniebraheem dynamicsofcovid19mathematicalmodelwithstochasticperturbation

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