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Epidemiol Infect. 2016 Oct;144(14):3080-3090. Epub 2016 Jul 13.

Exploratory social network analysis and gene sequencing in people who inject drugs infected with hepatitis C virus.

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School of Public Health,Wuhan University,Wuhan,Hubei,China.
Department of Epidemiology,Johns Hopkins Bloomberg School of Public Health,Baltimore,MD,USA.
Wuhan Centers for Disease Control & Prevention,Wuhan,Hubei,China.
Institute of Basic Medical Sciences,Wuhan University,Wuhan,Hubei,China.
Departments of Nursing,Hubei University of Chinese Medicine,Wuhan,Hubei,China.
College of Heath science and Nursing,Wuhan Polytechnic University,Wuhan,Hubei,China.


Social networks facilitate the transmission of hepatitis C virus (HCV) in people who inject drugs (PWID). The aim of this study was to assess how certain network structural characteristics are related to HCV infections in PWID and to determine the most susceptible individuals for HCV transmission in a network of PWID. PWID (N = 80) from central China were recruited from a previous follow-up case-control study. Demographic and behavioural information was obtained from a computerized database for each group. HCV RNA was extracted from blood specimens. Sequences were used to construct a phylogenetic tree and to determine genetic distances. Socio-metric social links were established between participants. Network measures were calculated using UCINET. Three HCV genotypes were identified, covering five subtypes. The density of the social networks for the whole sample (N = 80), case group (n = 31) and control group (n = 49) was 0.038, 0.054 and 0.008, respectively. PWID infected with HCV were in frequent contact with others within their group. There were four pairs of nodes with genotypic distances of 0.000 that were identified and clustered in subtypes 6a and 1b; each subject pair was linked and found in one clique. Three of the five most active nodes were infected with HCV. These three nodes served as a bridge, contributing to the connection of other nodes. These findings identify susceptible individuals for HCV transmission in PWID based on their frequent contact with others in the network. These results provide data that could be used for modelling HCV transmission patterns and in public health policies.


Genetic diversity; hepatitis C virus infection; people who inject drugs; social network analysis

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