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Optimal control strategy analysis for an human-animal brucellosis infection model with multiple delays

Firstly, we consider an animal-human infection model of brucellosis with three distributed delays, representing the latent period of brucellosis in infected animal and human population and the survival time of brucella in the environment, respectively. The equilibrium points and basic reproduction n...

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Detalles Bibliográficos
Autores principales: Wu, Man, Abdurahman, Xamxinur, Teng, Zhidong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9763851/
https://www.ncbi.nlm.nih.gov/pubmed/36561671
http://dx.doi.org/10.1016/j.heliyon.2022.e12274
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author Wu, Man
Abdurahman, Xamxinur
Teng, Zhidong
author_facet Wu, Man
Abdurahman, Xamxinur
Teng, Zhidong
author_sort Wu, Man
collection PubMed
description Firstly, we consider an animal-human infection model of brucellosis with three distributed delays, representing the latent period of brucellosis in infected animal and human population and the survival time of brucella in the environment, respectively. The equilibrium points and basic reproduction number [Formula: see text] are calculated. By building appropriate Lyapunov functionals and applying LaSalle's invariance principle, the sufficient conditions for global asymptotic stability of two equilibria are given. Secondly, by introducing four control variables, we set the corresponding optimal control model and drive the first order necessary conditions for the existence of optimal control solution. Finally, we perform several numerical simulations to validate our theoretical results and show effects of different control strategies.
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spelling pubmed-97638512022-12-21 Optimal control strategy analysis for an human-animal brucellosis infection model with multiple delays Wu, Man Abdurahman, Xamxinur Teng, Zhidong Heliyon Research Article Firstly, we consider an animal-human infection model of brucellosis with three distributed delays, representing the latent period of brucellosis in infected animal and human population and the survival time of brucella in the environment, respectively. The equilibrium points and basic reproduction number [Formula: see text] are calculated. By building appropriate Lyapunov functionals and applying LaSalle's invariance principle, the sufficient conditions for global asymptotic stability of two equilibria are given. Secondly, by introducing four control variables, we set the corresponding optimal control model and drive the first order necessary conditions for the existence of optimal control solution. Finally, we perform several numerical simulations to validate our theoretical results and show effects of different control strategies. Elsevier 2022-12-07 /pmc/articles/PMC9763851/ /pubmed/36561671 http://dx.doi.org/10.1016/j.heliyon.2022.e12274 Text en © 2022 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Wu, Man
Abdurahman, Xamxinur
Teng, Zhidong
Optimal control strategy analysis for an human-animal brucellosis infection model with multiple delays
title Optimal control strategy analysis for an human-animal brucellosis infection model with multiple delays
title_full Optimal control strategy analysis for an human-animal brucellosis infection model with multiple delays
title_fullStr Optimal control strategy analysis for an human-animal brucellosis infection model with multiple delays
title_full_unstemmed Optimal control strategy analysis for an human-animal brucellosis infection model with multiple delays
title_short Optimal control strategy analysis for an human-animal brucellosis infection model with multiple delays
title_sort optimal control strategy analysis for an human-animal brucellosis infection model with multiple delays
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9763851/
https://www.ncbi.nlm.nih.gov/pubmed/36561671
http://dx.doi.org/10.1016/j.heliyon.2022.e12274
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