Optimal control strategies on HIV/AIDS and pneumonia co-infection with mathematical modelling approach.

IF 1.8 4区 数学 Q3 ECOLOGY Journal of Biological Dynamics Pub Date : 2024-12-01 Epub Date: 2023-12-22 DOI:10.1080/17513758.2023.2288873
Shewafera Wondimagegnhu Teklu, Birhanu Baye Terefe, Dejen Ketema Mamo, Yohannes Fissha Abebaw
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Abstract

In this paper, a compartmental model on the co-infection of pneumonia and HIV/AIDS with optimal control strategies was formulated using the system of ordinary differential equations. Using qualitative methods, we have analysed the mono-infection and HIV/AIDS and pneumonia co-infection models. We have computed effective reproduction numbers by applying the next-generation matrix method, applying Castillo Chavez criteria the models disease-free equilibrium points global stabilities were shown, while we have used the Centre manifold criteria to determine that the pneumonia infection and pneumonia and HIV/AIDS co-infection exhibit the phenomenon of backward bifurcation whenever the corresponding effective reproduction number is less than unity. We carried out the numerical simulations to investigate the behaviour of the co-infection model solutions. Furthermore, we have investigated various optimal control strategies to predict the best control strategy to minimize and possibly to eradicate the HIV/AIDS and pneumonia co-infection from the community.

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用数学建模方法优化艾滋病毒/艾滋病和肺炎合并感染的控制策略。
本文利用常微分方程系统,建立了肺炎和艾滋病毒/艾滋病合并感染的分区模型,并提出了最佳控制策略。我们使用定性方法分析了单一感染模型和艾滋病毒/艾滋病与肺炎共同感染模型。我们运用新一代矩阵法计算了有效繁殖数,运用卡斯蒂略-查韦斯准则显示了模型无病平衡点的全局稳定性,同时我们运用中心流形准则确定,只要相应的有效繁殖数小于 1,肺炎感染和肺炎与艾滋病毒/艾滋病联合感染就会出现向后分叉现象。我们进行了数值模拟,以研究共同感染模型解的行为。此外,我们还研究了各种最佳控制策略,以预测最佳控制策略,从而最大限度地减少并可能根除社区中的艾滋病毒/艾滋病和肺炎合并感染。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Biological Dynamics
Journal of Biological Dynamics ECOLOGY-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
4.90
自引率
3.60%
发文量
28
审稿时长
33 weeks
期刊介绍: Journal of Biological Dynamics, an open access journal, publishes state of the art papers dealing with the analysis of dynamic models that arise from biological processes. The Journal focuses on dynamic phenomena at scales ranging from the level of individual organisms to that of populations, communities, and ecosystems in the fields of ecology and evolutionary biology, population dynamics, epidemiology, immunology, neuroscience, environmental science, and animal behavior. Papers in other areas are acceptable at the editors’ discretion. In addition to papers that analyze original mathematical models and develop new theories and analytic methods, the Journal welcomes papers that connect mathematical modeling and analysis to experimental and observational data. The Journal also publishes short notes, expository and review articles, book reviews and a section on open problems.
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