Human Immunodeficiency Virus (HIV) remains a major public health challenge in Indonesia, including Makassar City. This study aims to estimate and map the relative risk (RR) of HIV cases in Makassar City using the Bayesian spatial Conditional Autoregressive (CAR) Leroux model. The dataset comprises the number of HIV cases and the population of each district, with covariates including distance to the city center and population density. Results of Moran's I test indicated significant spatial autocorrelation in HIV cases across Makassar City. Model selection based on the Deviance Information Criterion (DIC) and Watanabe-Akaike Information Criterion (WAIC) identified the optimal model as the CAR Leroux with an Invers-Gamma (IG) hyperprior (0.5;0.0005) and distance as a covariate, yielding the lowest DIC and WAIC values. The estimation results demonstrated that distance is negatively associated with HIV incidence. The highest RR was observed in Ujung Pandang district, while the lowest was in Biringkanaya District. These findings may provide a basis for identifying priority intervention areas and support the development of more targeted and effective HIV elimination strategies.
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