Efficiency of Respondent-Driven Sampling for Identifying Men Who Inject Drugs Living with HIV and/or Hepatitis C over Time in Varanasi, India

BACKGROUND: People who inject drugs (PWID) face disproportionate burdens of HIV and hepatitis C (HCV) yet remain underserved by services. In India, population-level data on HIV/HCV prevalence and service engagement among PWID remain scarce. Respondent-driven sampling (RDS) enables population-level inference, however evidence on RDS performance with non-fixed sample sizes remains limited. METHODS: We examined RDS performance from December 2017 to December 2018 among PWID in Varanasi, India. Participants completed HIV and HCV testing and interviewer-administered surveys on service engagement. Using RDS-II weights, we estimated HIV/HCV prevalence and care continuum outcomes, and analyzed trends across enrollment quarters. RESULTS: RDS recruited 1,249 men who inject drugs across 22 waves. HIV prevalence was 7%, HCV prevalence was 12%. Overall, 6% were living with HIV/HCV co-infection. Two initial seeds were HIV and HCV negative. HIV positivity was 36% in Q1 declining to 1% in Q4; HCV positivity declined from 46% in Q1 to 3% in Q4. Service utilization was low, yet highest in Q1. Among participants living with HIV, 33% were aware of their status, 15% on antiretroviral therapy, and 11% virally suppressed. HCV care engagement was lower, with 3% aware of their status and 2% having initiated care. CONCLUSION: RDS identified PWID living with HIV/HCV most efficiently in Q1, highlighting how time-sensitive RDS methodology may be. Identifying well-connected seeds can be pivotal for early case detection. Monitoring recruitment trends may optimize case-finding and improve linkage to care using RDS, supporting efforts to improve quality of life for PWID and manage global HIV and HCV burdens.