Modelling a disease-relevant contact network of people who inject drugs

Rolls, David A., Wang, Peng, Jenkinson, Rebecca, Pattison, Phillipa E., Robins, Garry L., Sacks-Davis, Rachel, Daraganova, Galina, Hellard, Margaret, and McBryde, Emma (2013) Modelling a disease-relevant contact network of people who inject drugs. Social Networks, 35 (4). pp. 699-710.

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This study uses social network analysis to model a contact network of people who inject drugs (PWID)relevant for investigating the spread of an infectious disease (hepatitis C). Using snowball sample data, parameters for an exponential random graph model (ERGM) including social circuit dependence and four attributes (location, age, injecting frequency, gender) are estimated using a conditional estimation approach that respects the structure of snowball sample designs. Those network parameter estimates are then used to create a novel, model-dependent estimate of network size. Simulated PWID contact networks are created and compared with Bernoulli graphs. Location, age and injecting frequency are shown to be statistically significant attribute parameters in the ERGM. Simulated ERGM networks are shown to fit the collected data very well across a number of metrics. In comparison with Bernoulli graphs, simulated networks are shown to have longer paths and more clustering. Results from this study make possible simulation of realistic networks for investigating treatment and intervention strategies for reducing hepatitis C prevalence.

Item ID: 40426
Item Type: Article (Research - C1)
ISSN: 0378-8733
Keywords: exponential random graph model; hidden population; network size; snowball sample; social network
Funders: Australian Research Council (ARC), National Health and Medical Research Council of Australia (NHMRC)
Projects and Grants: ARC Grant DP0987730, NHMRC Project 331312, NHMRC Capacity Building Grant 358425
Date Deposited: 16 Sep 2015 01:08
FoR Codes: 11 MEDICAL AND HEALTH SCIENCES > 1103 Clinical Sciences > 110309 Infectious Diseases @ 40%
11 MEDICAL AND HEALTH SCIENCES > 1117 Public Health and Health Services > 111706 Epidemiology @ 40%
16 STUDIES IN HUMAN SOCIETY > 1605 Policy and Administration > 160508 Health Policy @ 20%
SEO Codes: 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920109 Infectious Diseases @ 50%
92 HEALTH > 9202 Health and Support Services > 920207 Health Policy Evaluation @ 50%
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