Cargando…

Modeling the dynamics of novel coronavirus (COVID-19) via stochastic epidemic model

Novel coronavirus disease is a burning issue all over the world. Spreading of the novel coronavirus having the characteristic of rapid transmission whenever the air molecules or the freely existed virus includes in the surrounding and therefore the spread of virus follows a stochastic process instea...

Descripción completa

Detalles Bibliográficos
Autores principales: Hussain, Ghulam, Khan, Tahir, Khan, Amir, Inc, Mustafa, Zaman, Gul, Nisar, Kottakkaran Sooppy, Akgül, Ali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7938760/
http://dx.doi.org/10.1016/j.aej.2021.02.036
_version_ 1783661650258165760
author Hussain, Ghulam
Khan, Tahir
Khan, Amir
Inc, Mustafa
Zaman, Gul
Nisar, Kottakkaran Sooppy
Akgül, Ali
author_facet Hussain, Ghulam
Khan, Tahir
Khan, Amir
Inc, Mustafa
Zaman, Gul
Nisar, Kottakkaran Sooppy
Akgül, Ali
author_sort Hussain, Ghulam
collection PubMed
description Novel coronavirus disease is a burning issue all over the world. Spreading of the novel coronavirus having the characteristic of rapid transmission whenever the air molecules or the freely existed virus includes in the surrounding and therefore the spread of virus follows a stochastic process instead of deterministic. We assume a stochastic model to investigate the transmission dynamics of the novel coronavirus. To do this, we formulate the model according to the charectersitics of the corona virus disease and then prove the existence as well as the uniqueness of the global positive solution to show the well posed-ness and feasibility of the problem. Following the theory of dynamical systems as well as by constructing a suitable stochastic Lyapunov function, we establish sufficient conditions of the extinction and the existence of stationary distribution. Finally, we carry out the large scale numerical simulations to demonstrate the verification of our analytical results.
format Online
Article
Text
id pubmed-7938760
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University.
record_format MEDLINE/PubMed
spelling pubmed-79387602021-03-09 Modeling the dynamics of novel coronavirus (COVID-19) via stochastic epidemic model Hussain, Ghulam Khan, Tahir Khan, Amir Inc, Mustafa Zaman, Gul Nisar, Kottakkaran Sooppy Akgül, Ali Alexandria Engineering Journal Article Novel coronavirus disease is a burning issue all over the world. Spreading of the novel coronavirus having the characteristic of rapid transmission whenever the air molecules or the freely existed virus includes in the surrounding and therefore the spread of virus follows a stochastic process instead of deterministic. We assume a stochastic model to investigate the transmission dynamics of the novel coronavirus. To do this, we formulate the model according to the charectersitics of the corona virus disease and then prove the existence as well as the uniqueness of the global positive solution to show the well posed-ness and feasibility of the problem. Following the theory of dynamical systems as well as by constructing a suitable stochastic Lyapunov function, we establish sufficient conditions of the extinction and the existence of stationary distribution. Finally, we carry out the large scale numerical simulations to demonstrate the verification of our analytical results. THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. 2021-08 2021-03-08 /pmc/articles/PMC7938760/ http://dx.doi.org/10.1016/j.aej.2021.02.036 Text en © 2021 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. 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
Hussain, Ghulam
Khan, Tahir
Khan, Amir
Inc, Mustafa
Zaman, Gul
Nisar, Kottakkaran Sooppy
Akgül, Ali
Modeling the dynamics of novel coronavirus (COVID-19) via stochastic epidemic model
title Modeling the dynamics of novel coronavirus (COVID-19) via stochastic epidemic model
title_full Modeling the dynamics of novel coronavirus (COVID-19) via stochastic epidemic model
title_fullStr Modeling the dynamics of novel coronavirus (COVID-19) via stochastic epidemic model
title_full_unstemmed Modeling the dynamics of novel coronavirus (COVID-19) via stochastic epidemic model
title_short Modeling the dynamics of novel coronavirus (COVID-19) via stochastic epidemic model
title_sort modeling the dynamics of novel coronavirus (covid-19) via stochastic epidemic model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7938760/
http://dx.doi.org/10.1016/j.aej.2021.02.036
work_keys_str_mv AT hussainghulam modelingthedynamicsofnovelcoronaviruscovid19viastochasticepidemicmodel
AT khantahir modelingthedynamicsofnovelcoronaviruscovid19viastochasticepidemicmodel
AT khanamir modelingthedynamicsofnovelcoronaviruscovid19viastochasticepidemicmodel
AT incmustafa modelingthedynamicsofnovelcoronaviruscovid19viastochasticepidemicmodel
AT zamangul modelingthedynamicsofnovelcoronaviruscovid19viastochasticepidemicmodel
AT nisarkottakkaransooppy modelingthedynamicsofnovelcoronaviruscovid19viastochasticepidemicmodel
AT akgulali modelingthedynamicsofnovelcoronaviruscovid19viastochasticepidemicmodel