An exploratory study using respondent-driven sampling to map HIV risk across sex work locations in Blantyre, Malawi

Background: Malawi has made notable progress in HIV control, with national prevalence currently at 8.9%. However, sub-populations 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 BlantyreSetting: Urban Blantyre, one of Malawi's 28 districts, focusing on the FSW population. 

Methods: 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. 

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