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

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