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Mathematical analysis of stochastic epidemic model of MERS-corona & application of ergodic theory
The “Middle East Respiratory” (MERS-Cov) is among the world’s dangerous diseases that still exist. Presently it is a threat to Arab countries, but it is a horrible prediction that it may propagate like COVID-19. In this article, a stochastic version of the epidemic model, MERS-Cov, is presented. Ini...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9805951/ https://www.ncbi.nlm.nih.gov/pubmed/36618952 http://dx.doi.org/10.1016/j.matcom.2022.12.023 |
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author | Hussain, Shah Tunç, Osman Rahman, Ghaus ur Khan, Hasib Nadia, Elissa |
author_facet | Hussain, Shah Tunç, Osman Rahman, Ghaus ur Khan, Hasib Nadia, Elissa |
author_sort | Hussain, Shah |
collection | PubMed |
description | The “Middle East Respiratory” (MERS-Cov) is among the world’s dangerous diseases that still exist. Presently it is a threat to Arab countries, but it is a horrible prediction that it may propagate like COVID-19. In this article, a stochastic version of the epidemic model, MERS-Cov, is presented. Initially, a mathematical form is given to the dynamics of the disease while incorporating some unpredictable factors. The study of the underlying model shows the existence of positive global solution. Formulating appropriate Lyapunov functionals, the paper will also explore parametric conditions which will lead to the extinction of the disease from a community. Moreover, to reveal that the infection will persist, ergodic stationary distribution will be carried out. It will also be shown that a threshold quantity exists, which will determine some essential parameters for exploring other dynamical aspects of the main model. With the addition of some examples, the underlying stochastic model of MERS-Cov will be studied graphically for more illustration. |
format | Online Article Text |
id | pubmed-9805951 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98059512023-01-04 Mathematical analysis of stochastic epidemic model of MERS-corona & application of ergodic theory Hussain, Shah Tunç, Osman Rahman, Ghaus ur Khan, Hasib Nadia, Elissa Math Comput Simul Original Articles The “Middle East Respiratory” (MERS-Cov) is among the world’s dangerous diseases that still exist. Presently it is a threat to Arab countries, but it is a horrible prediction that it may propagate like COVID-19. In this article, a stochastic version of the epidemic model, MERS-Cov, is presented. Initially, a mathematical form is given to the dynamics of the disease while incorporating some unpredictable factors. The study of the underlying model shows the existence of positive global solution. Formulating appropriate Lyapunov functionals, the paper will also explore parametric conditions which will lead to the extinction of the disease from a community. Moreover, to reveal that the infection will persist, ergodic stationary distribution will be carried out. It will also be shown that a threshold quantity exists, which will determine some essential parameters for exploring other dynamical aspects of the main model. With the addition of some examples, the underlying stochastic model of MERS-Cov will be studied graphically for more illustration. International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. 2023-05 2023-01-02 /pmc/articles/PMC9805951/ /pubmed/36618952 http://dx.doi.org/10.1016/j.matcom.2022.12.023 Text en © 2022 International Association for Mathematics and Computers in Simulation (IMACS). Published by 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 | Original Articles Hussain, Shah Tunç, Osman Rahman, Ghaus ur Khan, Hasib Nadia, Elissa Mathematical analysis of stochastic epidemic model of MERS-corona & application of ergodic theory |
title | Mathematical analysis of stochastic epidemic model of MERS-corona & application of ergodic theory |
title_full | Mathematical analysis of stochastic epidemic model of MERS-corona & application of ergodic theory |
title_fullStr | Mathematical analysis of stochastic epidemic model of MERS-corona & application of ergodic theory |
title_full_unstemmed | Mathematical analysis of stochastic epidemic model of MERS-corona & application of ergodic theory |
title_short | Mathematical analysis of stochastic epidemic model of MERS-corona & application of ergodic theory |
title_sort | mathematical analysis of stochastic epidemic model of mers-corona & application of ergodic theory |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9805951/ https://www.ncbi.nlm.nih.gov/pubmed/36618952 http://dx.doi.org/10.1016/j.matcom.2022.12.023 |
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