Spatial Analysis of the Determinants of HIV/AIDS Among Females Aged 15–34 in KwaZulu Natal, South Africa Using a Bayesian Spatial Logistic Regression Model

HIV remains a major public health challenge in sub-Saharan Africa, with South Africa bearing the highest burden. KwaZulu-Natal (KZN) has been identified as a hotspot, particularly among females aged 15–34. This study aimed to investigate the spatial distribution and key socio-demographic, behavioural, and economic factors associated with HIV prevalence among females in this age group using a Bayesian spatial logistic regression model. We analysed secondary data from 3324 females who participated in the HIV Incidence Provincial Surveillance System (HIPSS) from June 2014 to July 2015 in uMgungundlovu District, KZN. Bayesian spatial models were fitted using the Integrated Nested Laplace Approximation (INLA) to identify key predictors and spatial clusters of HIV prevalence. Results revealed that age, education, marital status, in-come, alcohol use, condom use, and number of sexual partners significantly influenced HIV prevalence. Higher age groups (20–34 years) had increased odds of HIV infection compared to those aged 15–19. Alcohol use, multiple partners, and STI/TB diagnosis elevated risk, whereas tertiary education and condom use were protective. Two HIV hotspots were identified, with one near Greater Edendale being statistically significant. Findings highlight the need for targeted, context-specific interventions to reduce HIV transmission among young females in KZN.