Bridging Epidemiology and System Dynamics Modeling to Better Understand HCV Risk Among Young People Who Inject Drugs

Background Injection drug use is the leading risk factor for hepatitis C virus (HCV) transmission in the US. Despite the knowledge of the risk factors for HCV among people who inject drugs (PWID), there is a need to better understand how these multiple factors interact and impact young PWID.MethodsData originated from a study of 539 New York City (NYC) residents ages 18-29 recruited via Respondent-Driven Sampling, who reported past-month nonmedical use of prescription opioids and/or heroin. Analyses are based on a subsample of 337 (62%) who reported injecting any drug 12 months prior to the interview. All variables were assessed via self-report, except HCV status, which was established via rapid antibody testing. Building on the statistical associations found we developed a qualitative system dynamics (SD) model to integrate into a single framework key risk and preventive factors for HCV.ResultsHCV antibody prevalence is 31% with an overall incidence of 10 per 100 person-years. HCV status was independently correlated with sharing cookers with two or more people (AOR=2.17); injecting drugs 4-6 years (AOR=2.49) and 7 or more (AOR=4.95); lifetime homelessness (AOR=2.52); and being incarcerated two or more times (AOR=1.99). The SD model facilitates identifying non-linearities and feedback loop structures not included in the statistical model and high leverage points such as harm reduction and HCV treatment that could ameliorate the spread of HCV.ConclusionsThe results may indicate an overall positive impact of harm reduction efforts in reducing HCV prevalence among young PWID in NYC while injection risks and structural factors remain areas of key concern. An SD approach contributes to a better understanding of how these risk factors interact and what policies could be effective in reducing HCV infections.