The Sociospatial Network: Risk and the Role of Place in the Transmission of Infectious Diseases
The Sociospatial Network: Risk and the Role of Place in the Transmission of Infectious Diseases
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DOI：
10.1371/journal.pone.0146915
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发表时间：
2016-02-03
期刊：
影响因子：
3.7
通讯作者：
Blanford, Justine I.
中科院分区：
文献类型：
--
作者：
Logan, James J.;Jolly, Ann M.;Blanford, Justine I.
控制性传播感染和血源性病原体具有挑战性，因为它们存在于表现出复杂社会互动的群体中。特别是，共用注射毒品使用设备和卖淫使人们处于高风险之中。先前研究社会网络中风险行为的工作表明，群体中人们的社会和地理距离有助于这些病原体的地方性。在这项研究中，我们通过受访者驱动的抽样选择，研究了在血源性和性传播病原体传播中，街道上的人的连通性中的位置的作用。2009年1月至12月在加拿大温尼伯招募了600名注射吸毒者、男男性行为者、街头青年和无家可归者作为样本。参与者的住所与其社会关系的住所相互联系，并与他们从事风险活动的地点联系在一起。调查答复确定了101个受访者参与注射吸毒或性交易的独特场所。风险地点和受访者的住所进行地理编码，以住所代表个人。通过网络图和地理信息系统（GIS）在空间上绘制了社会空间网络和最可能经常光顾的地理区域的估计。节点连接最多的网络占受访者的7.7%；考虑到社会空间网络，这一比例上升到了49.7%。网络中任何两个地点之间的平均距离在3.5公里以内。核密度估计揭示了五个最大网络重叠的关键活动空间。在这里，网络分析中空间和社会实体的结合定义了风险空间中弱势群体的重叠，超出了人与人之间的联系。这项工作的影响是深远的，不仅通过确定活动“热点”及其与每个社会网络的交集来了解性传播感染的传播动态，而且还有助于其他疾病（例如结核病）的传播和针对预防服务。
Control of sexually transmitted infections and blood-borne pathogens is challenging due to their presence in groups exhibiting complex social interactions. In particular, sharing injection drug use equipment and selling sex (prostitution) puts people at high risk. Previous work examining the involvement of risk behaviours in social networks has suggested that social and geographic distance of persons within a group contributes to these pathogens' endemicity. In this study, we examine the role of place in the connectedness of street people, selected by respondent driven sampling, in the transmission of blood-borne and sexually transmitted pathogens. A sample of 600 injection drug users, men who have sex with men, street youth and homeless people were recruited in Winnipeg, Canada from January to December, 2009. The residences of participants and those of their social connections were linked to each other and to locations where they engaged in risk activity. Survey responses identified 101 unique sites where respondents participated in injection drug use or sex transactions. Risk sites and respondents' residences were geocoded, with residence representing the individuals. The sociospatial network and estimations of geographic areas most likely to be frequented were mapped with network graphs and spatially using a Geographic Information System (GIS). The network with the most nodes connected 7.7% of respondents; consideration of the sociospatial network increased this to 49.7%. The mean distance between any two locations in the network was within 3.5 kilometres. Kernel density estimation revealed key activity spaces where the five largest networks overlapped. Here, the combination of spatial and social entities in network analysis defines the overlap of vulnerable populations in risk space, over and above the person to person links. Implications of this work are far reaching, not just for understanding transmission dynamics of sexually transmitted infections by identifying activity "hotspots" and their intersection with each social network, but also for the spread of other diseases (e.g. tuberculosis) and targeting prevention services.