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Malaria and COVID-19 co-dynamics: A mathematical model and optimal control
Malaria, one of the longest-known vector-borne diseases, poses a major health problem in tropical and subtropical regions of the world. Its complexity is currently being exacerbated by the emerging COVID-19 pandemic and the threats of its second wave and looming third wave. We formulate and analyze...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8249695/ https://www.ncbi.nlm.nih.gov/pubmed/34230748 http://dx.doi.org/10.1016/j.apm.2021.06.016 |
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author | Tchoumi, S.Y. Diagne, M.L. Rwezaura, H. Tchuenche, J.M. |
author_facet | Tchoumi, S.Y. Diagne, M.L. Rwezaura, H. Tchuenche, J.M. |
author_sort | Tchoumi, S.Y. |
collection | PubMed |
description | Malaria, one of the longest-known vector-borne diseases, poses a major health problem in tropical and subtropical regions of the world. Its complexity is currently being exacerbated by the emerging COVID-19 pandemic and the threats of its second wave and looming third wave. We formulate and analyze a mathematical model incorporating some epidemiological features of the co-dynamics of both malaria and COVID-19. Sufficient conditions for the stability of the malaria only and COVID-19 only sub-models’ equilibria are derived. The COVID-19 only sub-model has globally asymptotically stable equilibria while under certain condition, the malaria-only could undergo the phenomenon of backward bifurcation whenever the sub-model reproduction number is less than unity. The equilibria of the dual malaria-COVID19 model are locally asymptotically stable as global stability is precluded owing to the possible occurrence of backward bifurcation. Optimal control of the full model to mitigate the spread of both diseases and their co-infection are derived. Pontryagin’s Maximum Principle is applied to establish the existence of the optimal control problem and to derive the necessary conditions for optimal control of the diseases. Though this is not a case study, simulation results to support theoretical analysis of the optimal control suggests that concurrently applying malaria and COVID-19 protective measures could help mitigate their spread compared to applying each preventive control measure singly as the world continues to deal with this unprecedented and unparalleled COVID-19 pandemic. |
format | Online Article Text |
id | pubmed-8249695 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82496952021-07-02 Malaria and COVID-19 co-dynamics: A mathematical model and optimal control Tchoumi, S.Y. Diagne, M.L. Rwezaura, H. Tchuenche, J.M. Appl Math Model Article Malaria, one of the longest-known vector-borne diseases, poses a major health problem in tropical and subtropical regions of the world. Its complexity is currently being exacerbated by the emerging COVID-19 pandemic and the threats of its second wave and looming third wave. We formulate and analyze a mathematical model incorporating some epidemiological features of the co-dynamics of both malaria and COVID-19. Sufficient conditions for the stability of the malaria only and COVID-19 only sub-models’ equilibria are derived. The COVID-19 only sub-model has globally asymptotically stable equilibria while under certain condition, the malaria-only could undergo the phenomenon of backward bifurcation whenever the sub-model reproduction number is less than unity. The equilibria of the dual malaria-COVID19 model are locally asymptotically stable as global stability is precluded owing to the possible occurrence of backward bifurcation. Optimal control of the full model to mitigate the spread of both diseases and their co-infection are derived. Pontryagin’s Maximum Principle is applied to establish the existence of the optimal control problem and to derive the necessary conditions for optimal control of the diseases. Though this is not a case study, simulation results to support theoretical analysis of the optimal control suggests that concurrently applying malaria and COVID-19 protective measures could help mitigate their spread compared to applying each preventive control measure singly as the world continues to deal with this unprecedented and unparalleled COVID-19 pandemic. Elsevier Inc. 2021-11 2021-07-02 /pmc/articles/PMC8249695/ /pubmed/34230748 http://dx.doi.org/10.1016/j.apm.2021.06.016 Text en © 2021 Elsevier Inc. 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 | Article Tchoumi, S.Y. Diagne, M.L. Rwezaura, H. Tchuenche, J.M. Malaria and COVID-19 co-dynamics: A mathematical model and optimal control |
title | Malaria and COVID-19 co-dynamics: A mathematical model and optimal control |
title_full | Malaria and COVID-19 co-dynamics: A mathematical model and optimal control |
title_fullStr | Malaria and COVID-19 co-dynamics: A mathematical model and optimal control |
title_full_unstemmed | Malaria and COVID-19 co-dynamics: A mathematical model and optimal control |
title_short | Malaria and COVID-19 co-dynamics: A mathematical model and optimal control |
title_sort | malaria and covid-19 co-dynamics: a mathematical model and optimal control |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8249695/ https://www.ncbi.nlm.nih.gov/pubmed/34230748 http://dx.doi.org/10.1016/j.apm.2021.06.016 |
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