Modelling hepatitis C transmission over a social network of injecting drug users

Rolls, D.A., Daraganova, G., Sacks-Davis, R., Hellard, M., Jenkinson, R., McBryde, E., Pattison, P.E., and Robins, G.L. (2012) Modelling hepatitis C transmission over a social network of injecting drug users. Journal of Theoretical Biology, 297. pp. 73-87.

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Abstract

Hepatitis C virus (HCV) is a blood-borne virus that disproportionately affects people who inject drugs (PWIDs). Based on extensive interview and blood test data from a longitudinal study in Melbourne, Australia, we describe an individual-based transmission model for HCV spread amongst PWID. We use this model to simulate the transmission of HCV on an empirical social network of PWID. A feature of our model is that sources of infection can be both network neighbours and non-neighbours via "importing". Data-driven estimates of sharing frequency and rate of importing are provided. Compared to an appropriately calibrated fully connected network, the empirical network provides some protective effect on the time to primary infection. We also illustrate heterogeneities in incidence rate of infection, both across and within node degrees (i.e., number of network partners). We explore the reduced risk of infection from spontaneously clearing cutpoint nodes whose infection status oscillates, both in theory and in simulation. Further, we show our model-based estimate of per-event transmission probability largely agrees with previous estimates at the lower end of the range 1–3% commonly cited.

Item ID: 39756
Item Type: Article (Research - C1)
ISSN: 1095-8541
Keywords: agent-based; computer simulation; doubly stochastic; importing; spontaneous clearance
Funders: Australian Research Council (ARC), National Health and Medical Research Council of Australia (NHMRC)
Projects and Grants: ARC DP0987730, NHMRC Project 331312, NHMRC Capacity Building Grant 358425
Date Deposited: 08 Oct 2015 04:17
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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