Center for AIDS Intervention Research, Department of Psychiatry and Behavioral Medicine, Medical College of Wisconsin, Milwaukee, 53202, USA.
AIDS Behav. 2012 May;16(4):791-6. doi: 10.1007/s10461-011-0042-8.
Several mathematical modeling studies based on the concept of "HIV transmission rates" have recently appeared in the literature. The transmission rate for a particular group of HIV-infected persons is defined as the mean number of secondary infections per member of the group per unit time. This article reviews the fundamental principles and mathematics of transmission rate models; explicates the relationship between these models, Bernoullian models of HIV transmission, and mathematical models based on the concept of the "reproductive rate of infection"; describes an extension of existing transmission rate models to better incorporate the positive impact of HIV treatment; and discusses the limitations of the transmission rate modeling approach. Results from the extended transmission rate model indicate that approximately 51.6% of new sexually-transmitted infections in the US are due to the transmission risk behaviors of infected persons who are unaware of their infection, including 10.9% due to persons in the acute phase of HIV infection. Findings from this study suggest that significant reductions in HIV incidence likely will require a combination of increased antibody testing, enhanced early detection of acute HIV infection, appropriate medical care and antiretroviral medicine adherence counseling, and behavioral risk reduction interventions.
最近文献中出现了一些基于“HIV 传播率”概念的数学建模研究。特定组 HIV 感染者的传播率定义为单位时间内该组每个成员的平均二次感染数。本文回顾了传播率模型的基本原理和数学方法；阐述了这些模型与 HIV 传播的 Bernoulli 模型和基于“感染繁殖率”概念的数学模型之间的关系；描述了对现有传播率模型的扩展，以更好地纳入 HIV 治疗的积极影响；并讨论了传播率建模方法的局限性。扩展后的传播率模型的结果表明，美国大约有 51.6%的新性传播感染是由未意识到自己感染的感染者的传播风险行为造成的，其中 10.9%是由于处于 HIV 感染急性期的人造成的。这项研究的结果表明，要大幅减少 HIV 发病率，可能需要结合增加抗体检测、加强急性 HIV 感染的早期发现、适当的医疗保健和抗逆转录病毒药物依从性咨询，以及行为风险降低干预措施。
