评估阿片类药物使用障碍对注射毒品人群网络中艾滋病毒风险行为的溢出效应。

IF 0.9 Q4 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Stats Pub Date : 2024-06-01 Epub Date: 2024-06-19 DOI:10.3390/stats7020034
Joseph Puleo, Ashley Buchanan, Natallia Katenka, M Elizabeth Halloran, Samuel R Friedman, Georgios Nikolopoulos
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引用次数: 0

摘要

注射吸毒者(PWID)感染艾滋病毒的风险增加,部分原因是与阿片类药物使用有关的注射行为。阿片类药物使用障碍(mod)药物已被证明可以降低艾滋病毒感染风险,可能是通过减少注射风险行为。mod可能对那些自己不接受但通过社会、性或吸毒网络与接受治疗的人有联系的人有益。这就是所谓的溢出效应。网络研究中溢出效应的有效估计需要考虑网络的社区结构。社区是由紧密联系的个人组成的群体,与其他群体的联系很少。我们分析了来自减少传播干预项目的277名PWID及其联系人的网络。我们评估了mod对减少注射危险行为的影响,以及对接受mod治疗的参与者的网络接触可能带来的好处。我们使用基于模块化的方法确定社区,并使用反概率加权与社区水平倾向得分来调整测量的混淆。研究发现,mod对降低注射风险行为具有有益的溢出效应。估计影响的大小对社区检测方法敏感。在评价网络溢出效应的研究中,应充分考虑社区结构的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing Spillover Effects of Medications for Opioid Use Disorder on HIV Risk Behaviors among a Network of People Who Inject Drugs.

People who inject drugs (PWID) have an increased risk of HIV infection partly due to injection behaviors often related to opioid use. Medications for opioid use disorder (MOUD) have been shown to reduce HIV infection risk, possibly by reducing injection risk behaviors. MOUD may benefit individuals who do not receive it themselves but are connected through social, sexual, or drug use networks with individuals who are treated. This is known as spillover. Valid estimation of spillover in network studies requires considering the network's community structure. Communities are groups of densely connected individuals with sparse connections to other groups. We analyzed a network of 277 PWID and their contacts from the Transmission Reduction Intervention Project. We assessed the effect of MOUD on reductions in injection risk behaviors and the possible benefit for network contacts of participants treated with MOUD. We identified communities using modularity-based methods and employed inverse probability weighting with community-level propensity scores to adjust for measured confounding. We found that MOUD may have beneficial spillover effects on reducing injection risk behaviors. The magnitudes of estimated effects were sensitive to the community detection method. Careful consideration should be paid to the significance of community structure in network studies evaluating spillover.

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CiteScore
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