Role of direct and indirect social and spatial ties in the diffusion of HIV and HCV among people who inject drugs: a cross-sectional community-based network analysis in New Delhi, India.
Role of direct and indirect social and spatial ties in the diffusion of HIV and HCV among people who inject drugs: a cross-sectional community-based network analysis in New Delhi, India.
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直接和间接的社会和空间关系在注射药物的人中艾滋病毒和HCV传播中的作用：印度新德里的基于横断面的社区网络分析。
DOI：
10.7554/elife.69174
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发表时间：
2021-08-03
期刊：
影响因子：
7.7
通讯作者：
Solomon SS
中科院分区：
文献类型：
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作者：
Clipman SJ;Mehta SH;Srikrishnan AK;Zook KJ;Duggal P;Mohapatra S;Shanmugam S;Nandagopal P;Kumar MS;Ogburn E;Lucas GM;Latkin CA;Solomon SS
注射毒品的人(PWID)是一些最具爆炸性的人类免疫缺陷病毒(HIV)和丙型肝炎病毒(HCV)全球流行的罪魁祸首。虽然感染的个别驱动因素已被熟知，但对网络因素知之甚少，除了直接联系外，数据很少。印度新德里的2512名PWID是在2017-19年使用社交网络设计招募的。抽样开始于招募指定注射伙伴(前一个月与他们一起注射的人)的10名指标。然后，每个新兵按照相同的程序招募他们指定的注射伙伴，通过生物特征数据建立的跨网络联系。参与者回答了一项调查，包括注射地点的信息，并提供了血样。用Logistic回归分析与HIV/丙型肝炎病毒感染相关的因素。中位年龄为26岁；99%为男性。基线HIV感染率为37.0%，46.8%的人是活跃的丙型肝炎病毒感染者(丙型肝炎病毒RNA阳性)。艾滋病病毒和活动性丙型肝炎病毒感染的几率随着与感染者分离程度的增加而降低(艾滋病毒AOR：0.87；丙型肝炎病毒AOR：0.9)，而在特定地点注射的患者(艾滋病毒AOR：1.5；丙型肝炎病毒AOR：1.69)的几率增加，与个体水平的因素无关(p<；0.001)。此外，社交因素，例如，到受感染伴侣的网络距离，即使考虑到直接的自我中心关系，也是统计上有意义的预测因素。这些数据显示了艾滋病毒和丙型肝炎病毒感染的极高负担以及高度互联的注射和空间网络结构。将网络和空间数据纳入干预措施的设计/实施可能有助于中断传输，同时提高效率。国家药物滥用研究所和约翰霍普金斯大学艾滋病研究中心。了解连接人们的社会和空间关系是阻止传染病传播的关键因素。这些网络对于防治公共卫生干预难以触及的人群中的流行病特别重要。例如，基于网络的方法可以帮助阻止艾滋病毒或丙型肝炎在使用注射药物的人群中传播。然而，熟人、注射伙伴或首选吸毒场所等社会和地理联系如何影响感染风险仍未得到很好的规划。为了解决这个问题，Clipman等人。重点是印度新德里的注射吸毒者，这是一个受艾滋病毒和丙型肝炎严重影响的人群。超过2500人被招募，每个参与者都邀请他们的注射伴侣也参加。志愿者回答了调查问题，包括他们在哪里使用药物，并提供了要检测的血液样本。结果显示，即使在调整了个人风险因素后，人们在哪里使用药物，与谁在一起会影响他们感染艾滋病毒和丙型肝炎的风险。在社会关系方面，每一个人将给定的个人与感染者分开，感染艾滋病毒和丙型肝炎的可能性降低约13%。然而，地理网络也产生了重大影响。在热门地点注射，感染艾滋病毒和丙型肝炎的几率分别增加50%和69%。事实上，即使参与者没有在这些特定的地点吸毒，有注射伴侣吸毒也足以增加患病风险：每一个人从该地点分离一个人，感染艾滋病毒和丙型肝炎的可能性分别下降14%和10%。Clipman等人的结果。强调物理空间和社交网络之间的关系如何促成危险疾病在注射吸毒者中的传播。最终，这些知识可能有助于形成更好的公共卫生干预措施，考虑到地理位置的重要性。
People who inject drugs (PWID) account for some of the most explosive human immunodeficiency virus (HIV) and hepatitis C virus (HCV) epidemics globally. While individual drivers of infection are well understood, less is known about network factors, with minimal data beyond direct ties. 2512 PWID in New Delhi, India were recruited in 2017–19 using a sociometric network design. Sampling was initiated with 10 indexes who recruited named injection partners (people who they injected with in the prior month). Each recruit then recruited their named injection partners following the same process with cross-network linkages established by biometric data. Participants responded to a survey, including information on injection venues, and provided a blood sample. Factors associated with HIV/HCV infection were identified using logistic regression. The median age was 26; 99% were male. Baseline HIV prevalence was 37.0% and 46.8% were actively infected with HCV (HCV RNA positive). The odds of prevalent HIV and active HCV infection decreased with each additional degree of separation from an infected alter (HIV AOR: 0.87; HCV AOR: 0.90) and increased among those who injected at a specific venue (HIV AOR: 1.50; HCV AOR: 1.69) independent of individual-level factors (p<0.001). In addition, sociometric factors, for example, network distance to an infected alter, were statistically significant predictors even when considering immediate egocentric ties. These data demonstrate an extremely high burden of HIV and HCV infection and a highly interconnected injection and spatial network structure. Incorporating network and spatial data into the design/implementation of interventions may help interrupt transmission while improving efficiency. National Institute on Drug Abuse and the Johns Hopkins University Center for AIDS Research. Understanding the social and spatial relationships that connect people is a key element to stop the spread of infectious diseases. These networks are particularly relevant to combat epidemics among populations that are hard to reach with public health interventions. Network-based approaches, for example, can help to stop HIV or hepatitis C from spreading amongst populations that use injectable drugs. Yet how social and geographic connections such as acquaintances, injection partners, or preferred drug use places impact the risk of infection is still poorly mapped out. To address this question, Clipman et al. focused on people who inject drugs in New Delhi, India, a population heavily impacted by HIV and hepatitis C. Over 2500 people were recruited, each participant inviting their injection partners to also take part. The volunteers answered survey questions, including where they used drugs, and provided a blood sample to be tested. The results showed that, even after adjusting for individual risk factors, where people used drugs and with whom affected their risk of becoming infected with HIV and hepatitis C. In terms of social ties, the likelihood of HIV and hepatitis C infection decreased by about 13% for each person separating a given individual from an infected person. However, geographical networks also had a major impact. Injecting at a popular location respectively increased the odds of HIV and hepatitis C infection by 50% and 69%. In fact, even if the participant was not using drugs at these specific places, having an injection partner who did was enough to increase the risk for disease: for each person separating an individual from the location, the likelihood of being infected with HIV and hepatitis C decreased by respectively 14% and 10%. The results by Clipman et al. highlight how the relationships between physical spaces and social networks contribute to the spread of dangerous diseases amongst people who inject drugs. Ultimately, this knowledge may help to shape better public health interventions that would take into account the importance of geographical locations.