Public health targeting of PrEP at HIV positives' bridging networks

 描述（由申请人提供）：这项发展研究补助金（R21）要求资金，以探索在希腊雅典最近出现的艾滋病毒流行的公共卫生系统PrEP干预的可行性和影响。由于艾滋病毒流行病在全球大多数环境中已经趋于稳定或正在下降，新出现的流行病、重新出现的流行病或爆发将变得更加常见，特别是在发生影响艾滋病毒预防资源的社会、政治或其他“冲击”时。一个典型的例子是，2010年雅典采取紧缩措施后，最近在注射毒品者中流行。虽然已经观察到在PWID内限制流行方面取得了一些成功，但最近的系统发育和监测分析表明，来自最近PWID流行的HIV毒株（CRF35_AD，CRF14_BG，亚型A和B）已在2013年蔓延到MSM中（见初步研究）。 在新出现的流行病中，口服化学预防是预防易感人群感染性疾病的常用公共卫生策略。例如，在美国和欧洲的男男性接触者中，在侵袭性脑膜炎球菌病爆发时对性伴侣进行抗生素预防限制了新出现的爆发。同样，暴露前预防（PrEP）有可能用于新出现的流行病，以防止艾滋病毒的传播。虽然这种方法看起来很直观，但目前PrEP实施的概念仅限于使用专注于医疗服务提供者和客户之间个性化干预的临床模型。这是有问题的，因为由于缺乏适当的针对性，PrEP的公共卫生影响可能有限。事实上，从“现实世界”的PrEP使用的证据表明，风险较低的客户正在访问PrEP. As相比，资源密集型的临床试验或示范研究，仔细建模方法可以提供洞察到谁在一个新的艾滋病毒流行应该针对PrEP，以防止继续传播，以及用于识别这些人的策略，并将他们与护理。我们提出了一种建模方法，使用基于代理的模型（ABM），超越基本的病原体和传播模式，以处理复杂的社会互动，包括重叠的社会和性网络以及实施的现实，如有限的PrEP资源，延迟链接到PrEP护理和早期PreP护理保留根据经验收集的数据在希腊雅典。具体而言，我们的目标是：1）通过测量个人层面的风险因素，网络层面的连接和艾滋病毒系统发生簇来表征桥接MSM网络（n=250）; 2）在短期内测量未感染艾滋病毒的MSM子样本（n=50）的早期PrEP级联结果（艾滋病毒检测，PrEP与护理的联系）; 3）模拟这种有针对性的公共卫生PrEP干预对雅典艾滋病毒传播的影响。基于代理的模型，占经验的网络结构是最先进的艾滋病毒传播建模，并足够灵活，以解决谁应该接受PrEP，并最终如何网络PrEP干预可以影响新兴/重新出现的艾滋病毒流行病的基本问题。

 DESCRIPTION (provided by applicant): This developmental research grant award (R21) requests funds to explore the feasibility and impact of a public health system PrEP intervention in a recently emerging HIV epidemic in Athens Greece. As HIV epidemics in most settings globally have plateaued or are in decline, emerging epidemics, re-emerging epidemics or outbreaks will become more common, particularly when social, political or other "shocks" that impact HIV prevention resources occur. One well characterized example is the recent epidemic among people who inject drugs (PWID) that started in Athens following austerity measures in 2010. While some success in limiting the epidemic within PWID has been observed, recent phylogenetic and surveillance analysis demonstrates that the HIV strain from this most recent PWID epidemic (CRF35_AD, CRF14_BG, subtypes A and B) has spilled over into MSM in 2013 (see Preliminary Studies). In emerging epidemics, oral chemoprophylaxis is a commonly-used public health strategy to prevent infectious diseases in susceptible persons. For example, among US and European MSM, antibiotic prophylaxis for sex-partners in outbreaks of invasive meningococcal disease has limited emerging outbreaks. Similarly, pre-exposure prophylaxis (PrEP) has the potential to be used in emerging epidemics to prevent onwards HIV transmission. While this approach would seem intuitive, current conceptualizations of PrEP implementation narrowly use a clinical model focused on individualized intervention between health provider and client. This is problematic because the public health impact of PrEP may be limited due to lack of proper targeting. In fact, evidence from "real-world" PrEP use suggests that lower risk clients are accessing PrEP. As compared to resource intensive clinical trials or demonstration studies, careful modeling approaches can provide insight into who within a new HIV epidemic should be targeted for PrEP to prevent onward transmission as well as the strategies used to identify these individuals and link them to care. We propose a modeling approach using an Agent Based Model (ABM) that moves beyond basic pathogen and transmission patterns to dealing with complex social interactions, including overlapping social and sexual networks as well as implementation realities, like finite PrEP resources, delayed linkage to PrEP care and early PreP care retention based upon empirically collected data in Athens Greece. Specifically we aim to: 1) Characterize a bridging MSM network (n=250) by measuring individual-level risk factors, network-level connections, and HIV phylogenetic clusters; 2) Measure early PrEP cascade outcomes (HIV testing, PrEP linkage to care) of a sub-sample (n=50) of HIV uninfected MSM over the short term; and 3) Model the effects of this targeted public health PrEP intervention on HIV transmission in Athens. Agent-based models that account for empirical network structure are state-of- the-art in modeling HIV transmission and are flexible enough to address fundamental questions of who should receive PrEP and ultimately how a network-PrEP intervention can impact emerging/reemerging HIV epidemics.