Keywords
Abstract
ABSTRACT: This study aims to perform an analysis of the spatial distribution of confirmed dengue cases in the state of Piauí in 2022, using geoprocessing techniques and exploratory analysis of spatial data, including spatial statistics. The introduction emphasizes the importance of disease mapping for public health, mentioning the use of Geographic Information Systems (GIS) and geoprocessing techniques. The relevance of spatial statistics in analyzing the relationship between disease cases and their geographic locations is also mentioned.The methodology describes the data used, including the epidemiological records provided by the Information System for Notifiable Diseases (SINAN) and the population data provided by the Brazilian Institute of Geography and Statistics (IBGE). The software GeoDa is mentioned as the tool used for spatial statistical analysis of the data. Spatial analysis is addressed, with a focus on the rate of dengue cases per 100,000 inhabitants as a measure used in epidemiology to assess disease spread. The Global Moran's Index and the Local Moran's Index are then presented as spatial statistical techniques used to evaluate the spatial autocorrelation of dengue cases. In the results and discussion section, the spatial distribution of dengue incidence rate in the state of Piauí in 2022 is shown, indicating a higher incidence in the southeast region and highlighting the environmental and socioeconomic factors that contribute to disease propagation. Regarding the Moran's indices, the Global Moran's Index is presented, indicating a negative spatial autocorrelation but with a descriptive level that is not statistically significant. The Local Moran's Index is discussed in relation to the identification of significant spatial clusters, showing that some municipalities have a high incidence of dengue and neighboring areas with similar behavior.In the final remarks, the importance of analyzing the spatial distribution of dengue for public health authorities is emphasized, assisting in the identification of high-risk areas and guiding the implementation of preventive measures and entomological surveillance.