Thesis Topic Details

Topic ID:
Social network analysis of viral infections in prison settings
Fabio Luciani
Research Area:
Social simulation, System Modelling, Modelling
Associated Staff
Mike Bain
Topic Details
Group Suitable:
Molecular epidemiology and social network analysis to track HCV transmission in high-risk communities: injecting drug users in New South Wales prisons

Background and Aims
The hepatitis C Virus (HCV) epidemic is fuelled by transmission in high-risk communities, notably injecting drug users (IDU). Knowledge of the spatio-temporal and social factors characterizing IDU prison inmates is important for understanding and limiting the spread of HCV in the community at large and also for planning treatment strategies for high-risk individuals. By integrating information on risk behaviours, geographic location, and viral sequences, we have explored the relationship between recent transmissions and the social networks of injecting inmates in New South Wales prisons.
The Hepatitis C Incidence and Transmission Study (HITS) is a prospective cohort of high risk HCV uninfected prisoners followed during imprisonment. From this cohort, the timing of periods of imprisonment in the 30 NSW prisons, and the IDU risk behaviour was gathered by interview. Blood samples were collected at 6-12 month intervals for HCV antibody and RNA testing.
Phylogenetic analysis using the Neighbor Joining approach implemented in MEGA, was performed using viral sequences (N=146) of E1-HVR1 region of the HCV genome from 1-3 viraemic samples of 115 newly infected inmates within the HITS cohort. Clustering analysis was performed on the resulting trees using PhyloPart, where putative clusters are tested via measures of genetic distance between any pair of sequences. Finally, a social network was constructed using risk behaviour data from the prisoners to validate potential transmission hot-spots identified via phylogenetic analysis.
Clustering analysis revealed that in both Gt1 and Gt3 infected inmates there were multiple clusters of subjects with closely related sequences in the E1-HVR1 segment of the HCV genome, indicating evidence of transmission networks. These clusters were further corroborated by evidence that individual inmates within the identified clusters shared same prison location at the estimated time of infection and, in some cases, shared the same wing and cell.
A comprehensive molecular epidemiological analysis of HCV sequences in incident cases in conjunction with analysis of geographical and socio-behavioural factors has been completed providing a new understand the spatio-temporal epidemiology of HCV in IDU prisoners from NSW. The novel method integrates viral sequences and social network analysis to understand and quantify networks of HCV transmission.
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