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Stationary distribution and extinction of stochastic coronavirus (COVID-19) epidemic model

Similar to other epidemics, the novel coronavirus (COVID-19) spread very fast and infected almost two hundreds countries around the globe since December 2019. The unique characteristics of the COVID-19 include its ability of faster expansion through freely existed viruses or air molecules in the atm...

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Autores principales: Din, Anwarud, Khan, Amir, Baleanu, Dumitru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Published by Elsevier Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7311924/
https://www.ncbi.nlm.nih.gov/pubmed/32834596
http://dx.doi.org/10.1016/j.chaos.2020.110036
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author Din, Anwarud
Khan, Amir
Baleanu, Dumitru
author_facet Din, Anwarud
Khan, Amir
Baleanu, Dumitru
author_sort Din, Anwarud
collection PubMed
description Similar to other epidemics, the novel coronavirus (COVID-19) spread very fast and infected almost two hundreds countries around the globe since December 2019. The unique characteristics of the COVID-19 include its ability of faster expansion through freely existed viruses or air molecules in the atmosphere. Assuming that the spread of virus follows a random process instead of deterministic. The continuous time Markov Chain (CTMC) through stochastic model approach has been utilized for predicting the impending states with the use of random variables. The proposed study is devoted to investigate a model consist of three exclusive compartments. The first class includes white nose based transmission rate (termed as susceptible individuals), the second one pertains to the infected population having the same perturbation occurrence and the last one isolated (quarantined) individuals. We discuss the model’s extinction as well as the stationary distribution in order to derive the the sufficient criterion for the persistence and disease’ extinction. Lastly, the numerical simulation is executed for supporting the theoretical findings.
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spelling pubmed-73119242020-06-24 Stationary distribution and extinction of stochastic coronavirus (COVID-19) epidemic model Din, Anwarud Khan, Amir Baleanu, Dumitru Chaos Solitons Fractals Article Similar to other epidemics, the novel coronavirus (COVID-19) spread very fast and infected almost two hundreds countries around the globe since December 2019. The unique characteristics of the COVID-19 include its ability of faster expansion through freely existed viruses or air molecules in the atmosphere. Assuming that the spread of virus follows a random process instead of deterministic. The continuous time Markov Chain (CTMC) through stochastic model approach has been utilized for predicting the impending states with the use of random variables. The proposed study is devoted to investigate a model consist of three exclusive compartments. The first class includes white nose based transmission rate (termed as susceptible individuals), the second one pertains to the infected population having the same perturbation occurrence and the last one isolated (quarantined) individuals. We discuss the model’s extinction as well as the stationary distribution in order to derive the the sufficient criterion for the persistence and disease’ extinction. Lastly, the numerical simulation is executed for supporting the theoretical findings. Published by Elsevier Ltd. 2020-10 2020-06-24 /pmc/articles/PMC7311924/ /pubmed/32834596 http://dx.doi.org/10.1016/j.chaos.2020.110036 Text en © 2020 Published by Elsevier Ltd. 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
Din, Anwarud
Khan, Amir
Baleanu, Dumitru
Stationary distribution and extinction of stochastic coronavirus (COVID-19) epidemic model
title Stationary distribution and extinction of stochastic coronavirus (COVID-19) epidemic model
title_full Stationary distribution and extinction of stochastic coronavirus (COVID-19) epidemic model
title_fullStr Stationary distribution and extinction of stochastic coronavirus (COVID-19) epidemic model
title_full_unstemmed Stationary distribution and extinction of stochastic coronavirus (COVID-19) epidemic model
title_short Stationary distribution and extinction of stochastic coronavirus (COVID-19) epidemic model
title_sort stationary distribution and extinction of stochastic coronavirus (covid-19) epidemic model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7311924/
https://www.ncbi.nlm.nih.gov/pubmed/32834596
http://dx.doi.org/10.1016/j.chaos.2020.110036
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