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Backward bifurcation and optimal control in a co-infection model for SARS-CoV-2 and ZIKV

In co-infection models for two diseases, it is mostly claimed that, the dynamical behavior of the sub-models usually predict or drive the behavior of the complete models. However, under a certain assumption such as, allowing incident co-infection with both diseases, we have a different observation....

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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/PMC8994284/
https://www.ncbi.nlm.nih.gov/pubmed/35433239
http://dx.doi.org/10.1016/j.rinp.2022.105481
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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 In co-infection models for two diseases, it is mostly claimed that, the dynamical behavior of the sub-models usually predict or drive the behavior of the complete models. However, under a certain assumption such as, allowing incident co-infection with both diseases, we have a different observation. In this paper, a new mathematical model for SARS-CoV-2 and Zika co-dynamics is presented which incorporates incident co-infection by susceptible individuals. It is worth mentioning that the assumption is missing in many existing co-infection models. We shall discuss the impact of this assumption on the dynamics of a co-infection model. The model also captures sexual transmission of Zika virus. The positivity and boundedness of solution of the proposed model are studied, in addition to the local asymptotic stability analysis. The model is shown to exhibit backward bifurcation caused by the disease-induced death rates and parameters associated with susceptibility to a second infection by those singly infected. Using Lyapunov functions, the disease free and endemic equilibria are shown to be globally asymptotically stable for [Formula: see text] , respectively. To manage the co-circulation of both infections effectively, under an endemic setting, time dependent controls in the form of SARS-CoV-2, Zika and co-infection prevention strategies are incorporated into the model. The simulations show that SARS-CoV-2 prevention could greatly reduce the burden of co-infections with Zika. Furthermore, it is also shown that prevention controls for Zika can significantly decrease the burden of co-infections with SARS-CoV-2.
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spelling pubmed-89942842022-04-11 Backward bifurcation and optimal control in a co-infection model for SARS-CoV-2 and ZIKV Omame, Andrew Abbas, Mujahid Onyenegecha, Chibueze P. Results Phys Article In co-infection models for two diseases, it is mostly claimed that, the dynamical behavior of the sub-models usually predict or drive the behavior of the complete models. However, under a certain assumption such as, allowing incident co-infection with both diseases, we have a different observation. In this paper, a new mathematical model for SARS-CoV-2 and Zika co-dynamics is presented which incorporates incident co-infection by susceptible individuals. It is worth mentioning that the assumption is missing in many existing co-infection models. We shall discuss the impact of this assumption on the dynamics of a co-infection model. The model also captures sexual transmission of Zika virus. The positivity and boundedness of solution of the proposed model are studied, in addition to the local asymptotic stability analysis. The model is shown to exhibit backward bifurcation caused by the disease-induced death rates and parameters associated with susceptibility to a second infection by those singly infected. Using Lyapunov functions, the disease free and endemic equilibria are shown to be globally asymptotically stable for [Formula: see text] , respectively. To manage the co-circulation of both infections effectively, under an endemic setting, time dependent controls in the form of SARS-CoV-2, Zika and co-infection prevention strategies are incorporated into the model. The simulations show that SARS-CoV-2 prevention could greatly reduce the burden of co-infections with Zika. Furthermore, it is also shown that prevention controls for Zika can significantly decrease the burden of co-infections with SARS-CoV-2. The Author(s). Published by Elsevier B.V. 2022-06 2022-04-09 /pmc/articles/PMC8994284/ /pubmed/35433239 http://dx.doi.org/10.1016/j.rinp.2022.105481 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.
Backward bifurcation and optimal control in a co-infection model for SARS-CoV-2 and ZIKV
title Backward bifurcation and optimal control in a co-infection model for SARS-CoV-2 and ZIKV
title_full Backward bifurcation and optimal control in a co-infection model for SARS-CoV-2 and ZIKV
title_fullStr Backward bifurcation and optimal control in a co-infection model for SARS-CoV-2 and ZIKV
title_full_unstemmed Backward bifurcation and optimal control in a co-infection model for SARS-CoV-2 and ZIKV
title_short Backward bifurcation and optimal control in a co-infection model for SARS-CoV-2 and ZIKV
title_sort backward bifurcation and optimal control in a co-infection model for sars-cov-2 and zikv
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8994284/
https://www.ncbi.nlm.nih.gov/pubmed/35433239
http://dx.doi.org/10.1016/j.rinp.2022.105481
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