Municipal Wealth and Spatial Clustering of Leprosy Incidence in Sao Paulo, Brazil (2017--2020): Evidence from BYM2 Modeling

BackgroundLeprosy remains a significant public health challenge in Brazil, with distinct spatial and temporal patterns reflecting underlying socioeconomic inequalities. This study investigated the association between municipal socio-territorial indicators and the geographic distribution of leprosy in Sao Paulo State. MethodsA total of 4,562 new leprosy cases reported across 645 municipalities from 2017-2020 were analyzed using Bayesian spatial modeling. The Besag-York-Mollie 2 (BYM2) model was implemented to estimate relative risk while accounting for spatial dependence, incorporating municipal wealth as a covariate. Expected case counts were calculated based on overall state incidence rates and local population sizes. Exceedance probabilities were computed to identify high-risk clusters using a threshold of relative risk >2.0. Results and DiscussionsRelative risk estimates ranged from 0.06 to 31.52 (median: 0.96), with substantial spatial heterogeneity across municipalities. Municipal wealth demonstrated a significant protective effect (posterior mean: -0.059, 95% CrI: -0.081 to -0.037), indicating lower leprosy incidence in economically advantaged areas. The mixing parameter ({varphi} = 0.517) revealed approximately equal contributions of structured spatial and unstructured random effects. High-risk clusters were predominantly concentrated in western and northern regions of the state. ConclusionsLeprosy distribution in Sao Paulo State exhibits significant spatial clustering associated with municipal wealth disparities. The persistent geographic patterns suggest sustained socioeconomic determinants affecting disease transmission. These findings support targeted public health interventions in identified high-risk areas and emphasize the importance of addressing structural inequalities in leprosy control strategies.