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A fractional order model for the co-interaction of COVID-19 and Hepatitis B virus

Fractional differential equations are beginning to gain widespread usage in modeling physical and biological processes. It is worth mentioning that the standard mathematical models of integer-order derivatives, including nonlinear models, do not constitute suitable framework in many cases. In this w...

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Autores principales: Omame, Andrew, Abbas, Mujahid, Onyenegecha, Chibueze P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier B.V. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9891848/
https://www.ncbi.nlm.nih.gov/pubmed/36748094
http://dx.doi.org/10.1016/j.rinp.2022.105498
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author Omame, Andrew
Abbas, Mujahid
Onyenegecha, Chibueze P.
author_facet Omame, Andrew
Abbas, Mujahid
Onyenegecha, Chibueze P.
author_sort Omame, Andrew
collection PubMed
description Fractional differential equations are beginning to gain widespread usage in modeling physical and biological processes. It is worth mentioning that the standard mathematical models of integer-order derivatives, including nonlinear models, do not constitute suitable framework in many cases. In this work, a mathematical model for COVID-19 and Hepatitis B Virus (HBV) co-interaction is developed and studied using the Atangana–Baleanu fractional derivative. The necessary conditions of the existence and uniqueness of the solution of the proposed model are studied. The local stability analysis is carried out when the reproduction number is less than one. Using well constructed Lyapunov functions, the disease free and endemic equilibria are proven to be globally asymptotically stable under certain conditions. Employing fixed point theory, the stability of the iterative scheme to approximate the solution of the model is discussed. The model is fitted to real data from the city of Wuhan, China, and important parameters relating to each disease and their co-infection, are estimated from the fitting. The approximate solutions of the model are compared using the integer and fractional order derivatives. The impact of the fractional derivative on the proposed model is also highlighted. The results proven in this paper illustrate that HBV and COVID-19 transmission rates can greatly impact the dynamics of the co-infection of both diseases. It is concluded that to control the co-circulation of both diseases in a population, efforts must be geared towards preventing incident infection with either or both diseases.
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spelling pubmed-98918482023-02-02 A fractional order model for the co-interaction of COVID-19 and Hepatitis B virus Omame, Andrew Abbas, Mujahid Onyenegecha, Chibueze P. Results Phys Article Fractional differential equations are beginning to gain widespread usage in modeling physical and biological processes. It is worth mentioning that the standard mathematical models of integer-order derivatives, including nonlinear models, do not constitute suitable framework in many cases. In this work, a mathematical model for COVID-19 and Hepatitis B Virus (HBV) co-interaction is developed and studied using the Atangana–Baleanu fractional derivative. The necessary conditions of the existence and uniqueness of the solution of the proposed model are studied. The local stability analysis is carried out when the reproduction number is less than one. Using well constructed Lyapunov functions, the disease free and endemic equilibria are proven to be globally asymptotically stable under certain conditions. Employing fixed point theory, the stability of the iterative scheme to approximate the solution of the model is discussed. The model is fitted to real data from the city of Wuhan, China, and important parameters relating to each disease and their co-infection, are estimated from the fitting. The approximate solutions of the model are compared using the integer and fractional order derivatives. The impact of the fractional derivative on the proposed model is also highlighted. The results proven in this paper illustrate that HBV and COVID-19 transmission rates can greatly impact the dynamics of the co-infection of both diseases. It is concluded that to control the co-circulation of both diseases in a population, efforts must be geared towards preventing incident infection with either or both diseases. The Author(s). Published by Elsevier B.V. 2022-06 2022-04-21 /pmc/articles/PMC9891848/ /pubmed/36748094 http://dx.doi.org/10.1016/j.rinp.2022.105498 Text en © 2022 The Author(s) 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
Omame, Andrew
Abbas, Mujahid
Onyenegecha, Chibueze P.
A fractional order model for the co-interaction of COVID-19 and Hepatitis B virus
title A fractional order model for the co-interaction of COVID-19 and Hepatitis B virus
title_full A fractional order model for the co-interaction of COVID-19 and Hepatitis B virus
title_fullStr A fractional order model for the co-interaction of COVID-19 and Hepatitis B virus
title_full_unstemmed A fractional order model for the co-interaction of COVID-19 and Hepatitis B virus
title_short A fractional order model for the co-interaction of COVID-19 and Hepatitis B virus
title_sort fractional order model for the co-interaction of covid-19 and hepatitis b virus
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9891848/
https://www.ncbi.nlm.nih.gov/pubmed/36748094
http://dx.doi.org/10.1016/j.rinp.2022.105498
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