Rahman S M Ashrafur, Vaidya Naveen K, Zou Xingfu
Department of Applied Mathematics, University of Western Ontario, London, Ontario N6A 5B7, Canada.
Department of Mathematics and Statistics, University of Missouri-Kansas City, MO 64110, USA.
Math Biosci. 2016 Oct;280:38-49. doi: 10.1016/j.mbs.2016.07.009. Epub 2016 Jul 27.
While studies on pre-exposure prophylaxis (PrEP) and post-exposure prophylaxis (PEP) have demonstrated substantial advantages in controlling HIV transmission, the overall benefits of the programs with early initiation of antiretroviral therapy (ART) have not been fully understood and are still on debate. Here, we develop an immunity-based (CD4+ T cell count based) mathematical model to study the impacts of early treatment programs on HIV epidemics and the overall community-level immunity. The model is parametrized using the HIV prevalence data from South Africa and fully analyzed for stability of equilibria and infection persistence criteria. Using our model, we evaluate the effects of early treatment on the new infection transmission, disease death, basic reproduction number, HIV prevalence, and the community-level immunity. Our model predicts that the programs with early treatments significantly reduce the new infection transmission and increase the community-level immunity, but the treatments alone may not be enough to eliminate HIV epidemics. These findings, including the community-level immunity, might provide helpful information for proper implementation of HIV treatment programs.
虽然关于暴露前预防(PrEP)和暴露后预防(PEP)的研究已证明在控制艾滋病毒传播方面具有显著优势,但早期启动抗逆转录病毒疗法(ART)项目的总体益处尚未得到充分理解,仍存在争议。在此,我们开发了一种基于免疫(基于CD4 + T细胞计数)的数学模型,以研究早期治疗项目对艾滋病毒流行以及社区层面总体免疫力的影响。该模型使用来自南非的艾滋病毒流行数据进行参数化,并对平衡点的稳定性和感染持续标准进行了全面分析。利用我们的模型,我们评估了早期治疗对新感染传播、疾病死亡、基本繁殖数、艾滋病毒流行率以及社区层面免疫力的影响。我们的模型预测,早期治疗项目可显著减少新感染传播并提高社区层面免疫力,但仅靠治疗可能不足以消除艾滋病毒流行。这些发现,包括社区层面的免疫力,可能为艾滋病毒治疗项目的合理实施提供有用信息。