Determinantes socioespaciais da incidência da tríplice arbovirose em Feira de Santana-Ba

Abstract

The dengue, zika, and chikungunya arboviruses, which are transmitted by the Aedes aegypti mosquito, are today a serious public health problem. This work aimed to analyze the socioeconomic and environmental determinants of the incidence of tripartite arbovirus in the city of Feira de Santana, Bahia, Brazil. This was an ecological study of a population nature, for the period from 2014 to 2017. Initially, an exploratory and descriptive study of the secondary data of the notified cases of arboviruses was carried out in the Sistema de Notificações e Agravos (SINAN), also with the socio-environmental data from IBGE, information of precipitation and temperature of the Instituto Nacional de Metereologia (INMET) and data from the Índice de Infestação por Aedes Aegypti (LIRAa) and vacant lots in the endemic center. Spatial statistics techniques, Moran indexes (global and local) were used to identify the spatial self-correlation of variables and the formation of clusters. The elaboration of the socio-environmental vulnerability model for tripartite arboviruses in the city of Feira de Santana was carried out by means of multicriteria analysis using the method Analytic Hierarchy Process (AHP), created by Saaty. There was a global autocorrelation of 5 analyzed variables. Clusters and risk areas were identified in peripheral neighborhoods that presented low normalized values for socio-environmental variables (sewage network, garbage collection and water supply), LIRAa and high wasteland index. Among the 50 neighborhoods analyzed, 34% had a high degree of vulnerability, 34% a medium degree of vulnerability and 32% a low degree of vulnerability. It was found that the peripheral neighborhoods with inadequate infrastructure fit into the degree of high vulnerability and the central and sparsely populated neighborhoods had a degree of medium and low vulnerability. Among the groups formed, it is confirmed that the areas located to the west and northeast of the city have the highest concentrations of neighborhoods with a high degree of vulnerability, and the neighborhoods in the central and adjacent areas have low and medium degree of vulnerability. The vulnerability model developed proved to be effective in identifying risk areas for the population and demonstrated the need for investments in infrastructure in the peripheral area of the city.