Hepatitis C virus transmission among people who inject drugs in rural United States: mathematical modeling study using stochastic agent-based network simulation (AJE-00824-2024).

Abstract

People who inject drugs (PWID) account for the majority of hepatitis C virus (HCV) infections in the United States. The injection-equipment-sharing network likely plays an important role in shaping the dynamics of HCV transmission. Recognizing the emerging HCV epidemic in rural communities, we developed an agent-based network simulation model of HCV transmission via injection-equipment-sharing and used data on rural PWID networks to inform model parameterization and calibration. We then simulated an array of networks that varied key network properties to understand their impact on the magnitude and distribution of HCV incidence. The results show substantial heterogeneity in HCV acquisition risks across the network, summarized using the Ghyaini coefficient. In addition, although PWID with fewer injection partners had lower incidence, they collectively acquired more infections due to their larger population size. Higher prevalence, average number of partners, and homophily in HCV infection were associated with lower heterogeneity in infection risk across the network and higher overall incidence; other network properties including population size did not have a substantial impact. Our findings illustrate the heterogeneity of HCV transmission among PWID and suggest key network properties that could be measured, evaluated, or considered in the design of interventions for PWID in future studies.