SPATIAL ANALYSIS OF LEPROSY CASES IN THE STATE OF PARÁ DURING THE PERIOD FROM 2014 TO 2024

Leprosy is an infectious disease caused by the bacterium Mycobacterium leprae. This disease is still prevalent worldwide, especially in Brazil, with several states presenting high rates, including the state of Pará. Therefore, this study aims to evaluate leprosy cases in the state of Pará during the period from 2014 to 2024 using spatial analysis methods. The study was conducted in the state of Pará between 2014 and 2024, using DATASUS data on leprosy and population by municipality. Spatial analysis was performed using the Global Moran’s Index in TerraView software, with map construction in a GIS environment. Results were obtained from two approaches: the first including all municipalities and the second excluding the municipality of Marituba, considered an outlier. In the complete analysis, the global Moran’s Index was 0.41108 (p-value=0.004), indicating moderate autocorrelation. After excluding Marituba, the index increased to 0.665387 (p-value=0.001), characterizing strong spatial autocorrelation. Results were significant, showing that the presence of the outlier reduced the strength of the spatial pattern. Analysis of scatterplots between standardized Z and WZ values complemented the findings by demonstrating consistency of autocorrelation. In the complete approach, the coefficient of determination was R ²=0.4545, indicating a moderate relationship between local values and those of their neighbors. With the exclusion of Marituba, this value increased to R ²=0.7091, demonstrating a stronger spatial relationship and reinforcing the impact of the outlier. Quadrant analysis of the boxmap reinforced the autocorrelation patterns identified by Moran’s Index. In the complete approach, 126 municipalities were in positive autocorrelation quadrants and 18 municipalities were classified as outliers. After excluding Marituba, an increase in positive clusters and a reduction in outliers were observed. This redistribution confirms the impact of the outlier on dispersion and reinforces cluster consistency, highlighting patterns of high and low incidence in the state. Leprosy in Pará presents a structured spatial pattern, with areas of high incidence and significant autocorrelation. Excluding Marituba strengthened the identification of priority clusters. The results reinforce the need for targeted control strategies and greater governmental support in the most vulnerable regions.