Department of Mathematics, Stockholm University, SE-10691 Stockholm, Sweden.
Department of Mathematics, Stockholm University, SE-10691 Stockholm, Sweden.
Epidemics. 2019 Jun;27:66-76. doi: 10.1016/j.epidem.2019.02.001. Epub 2019 Feb 2.
HIV is a sexually transmitted infection (STI) whose transmission process is highly dependent on the sexual network structure of the population under consideration. Most sexual behaviour data is egocentric in nature. We develop a stochastic dynamic sexual network model that utilises this type of egocentric network data. The model incorporates both steady and casual sex partners, and can be seen as a stochastic form of a generalised pair-formation model. We model the spread of an infection where individuals are susceptible, infectious, or successfully treated (and unable to transmit) and derive analytical expressions for several epidemiological quantities. We use sexual behaviour and HIV prevalence data that was gathered among 403 MSM at an STI clinic in Stockholm. To accurately capture transmission dynamics for this population, we need to explicitly model both casual sex partners and steady partnerships. Our model yields an estimate for the mean time until diagnosis followed by successful treatment that is in line with literature. This study indicates that small reductions in the time to diagnosis, and thereby, beginning of treatment, may substantially reduce HIV prevalence. Moreover, we find that moderate increases in condom use with casual sex partners have greater impact on reducing prevalence than the same increases in condom use with steady sex partners. This result demonstrates the relative importance of casual contacts on the HIV transmission dynamics among MSM in Sweden. Our results highlight the importance of HIV testing and condom-use interventions, and the role that casual and steady partners play in this, in order to turn the epidemiological trend in Sweden towards decreased HIV incidence.
艾滋病毒是一种性传播感染（STI），其传播过程高度依赖于所考虑人群的性网络结构。大多数性行为数据本质上是自我中心的。我们开发了一种随机动态性网络模型，该模型利用了这种自我中心的网络数据。该模型同时包含了固定性伴侣和偶然的性伴侣，可以被视为广义配对形成模型的一种随机形式。我们对一种感染的传播进行建模，其中个体是易感的、感染的或成功治疗（且无法传播）的，并推导出了几个流行病学数量的分析表达式。我们使用了在斯德哥尔摩的一家性传播感染诊所中收集的 403 名男男性行为者的性行为和艾滋病毒流行数据。为了准确捕捉该人群的传播动态，我们需要明确地对偶然的性伴侣和固定的伴侣关系进行建模。我们的模型得出了从诊断到成功治疗的平均时间的估计值，这与文献相符。这项研究表明，诊断时间的微小减少，即治疗的开始时间的减少，可能会大大降低艾滋病毒的流行率。此外，我们发现，偶然的性伴侣使用避孕套的适度增加，对降低流行率的影响大于与固定性伴侣使用避孕套的同等增加。这一结果表明了偶然接触在瑞典男男性行为者中的艾滋病毒传播动态中的相对重要性。我们的结果强调了艾滋病毒检测和避孕套使用干预的重要性，以及偶然和固定伴侣在这方面的作用，以扭转瑞典艾滋病毒发病率下降的趋势。
