Abstract
BACKGROUND AND OBJECTIVE: Periodic tracking of the trends and the levels of HIV prevalence at regional and district levels helps to strengthen a state's HIV/AIDS response. HIV prevalence among pregnant women is crucial for the HIV prevalence estimation of the general population. Karnataka is one of the high HIV prevalence states in India. Probing regional and district levels and trends of HIV prevalence provides critical insights into district-level epidemic patterns. This paper analyzes the region- and district-wise levels and trends of HIV prevalence among pregnant women attending the antenatal clinics (ANC) from 2003 to 2019 in Karnataka, South India. METHODS: HIV prevalence data collected from pregnant women in Karnataka during HIV Sentinel Surveillance (HSS) between 2003 and 2019 was used for trend analysis. The consistent sites were grouped into four zones (Bangalore, Belgaum, Gulbarga and Mysore regions), totaling 60 sites, including 30 urban and 30 rural sites. Regional and district-level HIV prevalence was calculated; trend analysis using Chi-square trend test and spatial analysis using QGIS software was done. For the last three HSS rounds, HIV prevalence based on sociodemographic variables was calculated to understand the factors contributing to HIV positivity in each region. RESULTS: In total, 254,563 pregnant women were recruited. HIV prevalence in Karnataka was 0.22 (OR: 0.15 95% CI: 0.16 - 0.28) in 2019. The prevalence was 0.24, 0.32, 0.17 and 0.14 in Bangalore, Belgaum, Gulbarga, and Mysore regions, respectively. HIV prevalence had significantly (P< 0.05) declined in 26 districts. CONCLUSION AND GLOBAL HEALTH IMPLICATIONS: HIV prevalence among pregnant women was comparatively higher in Bangalore and Belgaum regions. Analysis of contextual factors associated with the transmission risk and evidence-based targeted interventions will strengthen HIV management in Karnataka. Regionalized, disaggregated, sub-national analyses will help identify emerging pockets of infections, concentrated epidemic zones and contextual factors driving the disease transmission.