HTLV-2和HIV-1合并感染的宿主内动力学与延迟。

IF 1.8 4区 数学 Q3 ECOLOGY
Journal of Biological Dynamics Pub Date : 2025-12-01 Epub Date: 2025-05-21 DOI:10.1080/17513758.2025.2506536
A M Elaiw, E A Almohaimeed
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引用次数: 0

摘要

本文建立了HTLV-2和HIV-1与潜伏库、四种分布时滞和HIV-1特异性B细胞共同感染的数学模型。我们证明了系统的解保持有界和非负,辨识了系统的稳定状态,并给出了保证系统稳定状态存在和全局渐近稳定的充分条件。利用Lyapunov方法确定了系统的全局稳定性。我们提供了数值模拟来支持稳定性结果。对HTLV-2单感染(R1)和HIV-1单感染(R2)的基本繁殖数进行敏感性分析。我们研究了时间延迟如何影响HIV-1和HTLV-2之间的相互作用。模型中加入延迟项反映了抗病毒治疗的影响,有助于降低R1和R2,从而限制感染的传播。这突出了设计延长延迟期的治疗方法的潜力。纳入这些延迟提高了模型的精度,并支持更有效的评估治疗策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Within-host dynamics of HTLV-2 and HIV-1 co-infection with delay.

This paper formulates a mathematical model for the co-infection of HTLV-2 and HIV-1 with latent reservoirs, four types of distributed-time delays and HIV-1-specific B cells. We establish that the solutions remain bounded and nonnegative, identify the system's steady states, and derive sufficient conditions ensuring both their existence and global asymptotic stability. The system's global stability is confirmed using Lyapunov's method. We provide numerical simulations to support the stability results. Sensitivity analysis of basic reproduction numbers of HTLV-2 mono-infection (R1) and HIV-1 mono-infection (R2) is conducted. We examine how time delays influence the interaction between HIV-1 and HTLV-2. Including delay terms in the model reflects the influence of antiviral treatments, which help decrease R1 and R2, thus limiting the spread of infection. This highlights the potential for designing therapies that prolong delay period. Incorporating such delays improves model precision and supports more effective evaluation of treatment strategies.

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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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