Over the last years, the World Health Organization (WHO), the Pan American Health Organization (PAHO) and the Ministry of Health (MS) have been prioritizing geographic areas with high case detection and social determinants that increase the risk of illness of its inhabitants in favor of the geographic policies to combat the endemic leprosy. The current study aims to characterize the disease, its epidemiological, operational and socio-demographic variables and the policies developed for its control and elimination. Thus, there was a transversal, retrospective and descriptive study, on the population basis with a temporal and spatial analysis of new leprosy cases that was associated with the income population condition and the level of health services in three cities in the state of Pará : Ananindeua, Marabá and Xinguara. Using the digital cartographic basis and socioeconomic data of each city, developed by the Brazilian Institute of Geography and Statistics (IBGE) and the morbidity registered in the SINAN, the new cases diagnosed during the period of 2010 to 2015 were characterized, by census sector, aiming to subsidize the analysis, as well as intervention strategies. The Epi Info 7 and Bioestat 5.0 softwares were used for the statistical tests, in which it was hypothesized that there is a positive relationship between the epidemiological variables and the other ones. The cases were geographically referenced on site, using a Global Positioning System receiver (GPS) and theses very cases were specialized using a Geographic Information System (GIS). The Kernel estimation method was applied in order to obtain spatial analysis and aiming to highlight areas of higher case density and also where the best levels of patient care were found. The real risk of occurrence of leprosy in each area was analyzed using the Buffer technique, as from the incidence in children under 15 years old and multibacillary cases. Considering the problem and the use of the aforementioned methods and techniques, a collection of tables and graphs of the main indicators and the magnitude of the hidden prevalence of leprosy was generated, as well as a variety of digital images that express the disease spatial analysis. The results shown in thematic maps reveal an inhomogeneous distribution of leprosy in the territories, highlighting areas of greater and lower risk and allowing to identify those that could be taken as a priority by the Leprosy Control Program.
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