使用基于代理的性网络模型分析控制衣原体的缓解措施的影响
Using an agent-based sexual-network model to analyze the impact of mitigation efforts for controlling chlamydia
摘要：
沙眼衣原体（Ct）是美国报道最多的性传播感染，是女性不孕症和盆腔炎的主要原因。尽管数十年来对女性进行CT筛查，但年轻的非洲裔美国人（AA）的发病率仍在上升。我们创建并分析了一个基于代理的网络模型，以了解Ct的传播。我们校准模型参数，以符合调查数据显示，在路易斯安那州新奥尔良市的15-25岁的AA中，Ct患病率为12%的女性和10%的男性。我们的模式考虑到长期和临时的伙伴关系。该网络通过保留数据中观察到的联合度分布来捕获个体的重复混合。我们比较了随机筛查男性、伴侣通知（包括伴侣治疗、伴侣筛查和重新筛查感染）的干预策略的效率。我们比较了治疗感染者的伴侣时进行和不进行检测的差异。我们观察到，尽管增加Ct筛查、重新筛查和治疗感染者的大多数伴侣将降低患病率，但仅凭这些缓解措施不足以控制疫情。目前的做法是治疗受感染者的伴侣，而不首先检测他们是否感染。该模型预测，如果所有感染者的伴侣中有足够数量的人接受检测和治疗，那么就存在一个可以缓解流行病的阈值条件。这一阈值是由于通过治疗个体受感染伴侣的伴侣而建立的扩大治疗网络造成的。虽然这些结论可以帮助设计未来的Ct缓解研究，但我们提醒读者，这些结论是针对数学模型的，而不是现实世界，并且取决于模型假设的有效性。
英文摘要：
Chlamydia trachomatis (Ct) is the most reported sexually transmitted infection in the United States with a major cause of infertility and pelvic inflammatory disease among women. Despite decades of screening women for Ct, rates increase among young African Americans (AA). We create and analyze an agent-based network model to understand the spread of Ct. We calibrate the model parameters to agree with survey data showing Ct prevalence of 12% of the women and 10% of the men in the 15-25 year-old AA in New Orleans, Louisiana. Our model accounts for long-term and casual partnerships. The network captures assortative mixing of individuals by preserving the joint-degree distributions observed in the data. We compare the efficiency of intervention strategies of randomly screening men, partner notification, which includes partner treatment, partner screening, and rescreening for infection. We compare the difference between treating partners of an infected person both with and without testing them. We observe that although increased Ct screening, rescreening and treating most of the partners of infected people will reduce the prevalence, these mitigations alone are not sufficient to control the epidemic. The current practice is to treat the partners of an infected individual, without first testing them for infection. The model predicts that if a sufficient number of the partners of all infected people are tested and treated, then there is a threshold condition where the epidemic can be mitigated. This threshold results from the expanded treatment network created by treating the partners of the infected partners of an individual. Although these conclusions can help design future Ct mitigation studies, we caution the reader that these conclusions are for the mathematical model, not the real world, and are contingent on the validity of the model assumptions.
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