<b> </b><b> Bayesian Modeling</b>

<b>ABSTRACT</b><b>OBJECTIVE</b>Despite significant advancements in understanding risk factors and treatment strategies, ischemic heart disease (IHD) remains the leading cause of mortality worldwide, particularly within specific regions in Brazil where the disease is a burden. Therefore, the aim of this study was to estimate the risk of hospitalization and mortality from IHD in Paraná State, Brazil, using spatial analysis.<b>METHODS</b>This is an ecological study based on secondary and historical mortality data obtained from the Brazilian Mortality Information System and Hospitalization Information System during 2010-2021 period, stratified by Health Regions in Paraná State. To assess the spatial patterns of the disease and identify relative risk (RR) areas, we constructed a risk model by Bayesian inference using the R-INLA and SpatialEpi packages in R software. <b>RESULTS</b>A total of 333,229 hospitalizations and 73,221 deaths with elevated RR of 27.42 of hospitalizations and 15.68 of mortality for IHD in small-sized municipalities. Hospitalization and death rates were higher in men and whites aged 40-59. Regions 2 and 6 had the highest hospitalization risks, while all other regions presented RR of death &gt;1. The RR median of hospitalizations remained constant, but mortality median increased over time.<b>CONCLUSION </b>Areas with increased risk of hospitalization and mortality of IHD was found between small and medium municipalities in Parana State, Brazil. These results suggested that there is a deficit of care in health attention for IHD cases in small and medium-sized municipalities, which can be justified by a low distribution of healthcare resources.<br>