An Exploratory Study Using Respondent-Driven Sampling to Map HIV Risk Across Sex Work Locations in Blantyre, Malawi

Malawi has made notable progress in HIV control, with the national prevalence currently at 8.9%. However, subpopulations such as female sex workers (FSW) remain disproportionately affected. Respondent-driven sampling (RDS) enables access to such hard-to-reach populations, often underrepresented in traditional surveys. This study explored the feasibility of using RDS to assess geographic heterogeneity in HIV prevalence among FSW and identify high-risk hotspots in Blantyre.

Urban Blantyre, one of Malawi's 28 districts, focusing on the FSW population.

We recruited 223 FSW using RDS to estimate HIV risk profiles. Sex work venues were anonymized and grouped into zones A, B, C, and D. We calculated RDS-II-weighted HIV prevalence and 95% confidence intervals by zone. A multivariable logistic regression model, weighted for RDS design, was used to identify key risk factors for HIV positivity. We also generated maps of RDS-weighted prevalence to visualize the hotspots.

Overall HIV prevalence in urban Blantyre was 70% (95% CI: 57% to 83%), with observed heterogeneity across zones ranging from 56.0% (95% CI: 32.6% to 79.5%) to 77.7% (95% CI: 44.7% to 94.7%). After adjusting for confounders, zone D had the highest odds of HIV, followed by zones B and C, all compared with zone A thus highlighting varying risk profiles across the city.

RDS effectively captured spatial disparities in HIV burden among FSW in Blantyre. Clear geographic hotspots emerged, highlighting the need for targeted interventions in high-burden zones. Repeated RDS implementation could support ongoing surveillance and more efficient resource allocation.