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

In this article we propose a stochastic model to discuss the dynamics of novel corona virus disease. We formulate the model to study the long run behavior in varying population environment. For this purposes we divided the total human population into three epidemiological compartments: the susceptib...

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Detalles Bibliográficos
Autores principales: Khan, Tahir, Zaman, Gul, El-Khatib, Youssef
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier B.V. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7999738/
https://www.ncbi.nlm.nih.gov/pubmed/33816091
http://dx.doi.org/10.1016/j.rinp.2021.104004
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author Khan, Tahir
Zaman, Gul
El-Khatib, Youssef
author_facet Khan, Tahir
Zaman, Gul
El-Khatib, Youssef
author_sort Khan, Tahir
collection PubMed
description In this article we propose a stochastic model to discuss the dynamics of novel corona virus disease. We formulate the model to study the long run behavior in varying population environment. For this purposes we divided the total human population into three epidemiological compartments: the susceptible, covid-19 infected, recovered and recovered along with one class of reservoir. The existence and uniqueness of the newly formulated model will be studied to show the well-possedness of the model. Moreover, we investigate the extinction analysis as well as the persistence analysis to find the disease extinction and disease persistence conditions. At the end we perform simulation to justify the investigation of analytical work with the help of graphical representations.
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spelling pubmed-79997382021-03-29 Modeling the dynamics of novel coronavirus (COVID-19) via stochastic epidemic model Khan, Tahir Zaman, Gul El-Khatib, Youssef Results Phys Article In this article we propose a stochastic model to discuss the dynamics of novel corona virus disease. We formulate the model to study the long run behavior in varying population environment. For this purposes we divided the total human population into three epidemiological compartments: the susceptible, covid-19 infected, recovered and recovered along with one class of reservoir. The existence and uniqueness of the newly formulated model will be studied to show the well-possedness of the model. Moreover, we investigate the extinction analysis as well as the persistence analysis to find the disease extinction and disease persistence conditions. At the end we perform simulation to justify the investigation of analytical work with the help of graphical representations. The Authors. Published by Elsevier B.V. 2021-05 2021-03-27 /pmc/articles/PMC7999738/ /pubmed/33816091 http://dx.doi.org/10.1016/j.rinp.2021.104004 Text en © 2021 The Authors 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
Khan, Tahir
Zaman, Gul
El-Khatib, Youssef
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/PMC7999738/
https://www.ncbi.nlm.nih.gov/pubmed/33816091
http://dx.doi.org/10.1016/j.rinp.2021.104004
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