Análise espacial do padrão de introdução e disseminação da dengue nos municípios do Espírito Santo

Abstract

The number of cities infested by Aedes aegypti in Espírito Santo state is increasing, leading to high rates of dengue incidence over the years. Despite attempts to combat the disease, it has become a major concern in public health of this state. This study aims to describe the dynamics of the spread of the disease in the state based on the association between environmental variables and population, using data operationalized through Geographic Information System (GIS) techniques. The study used data source for vector mosquito infestation and the incidence rate of the disease, the inter-cities road distances, altitude of municipalities and geo-climatic variables (temperature and sufficiency of water), incorporated into an operational tool, Unidades Naturais do Espírito Santo (UNES), represented on a single map operationalized in GIS, obtained from Integrated and Georeferenced Bases of Espirito Santo. For data analysis, we performed a Poisson regression for data about dengue incidence and Logistic Regression for infestation by the vector. Then, the data on infestation by mosquitoes and dengue incidence were georeferenced using GIS ArcGIS version 9.2 as an operational tool. It was observed that rainfall is a factor that contributes to the emergence of the mosquito in an uninfested area. High temperatures contribute to a high incidence rate of dengue in the cities of Espírito Santo. The variable “distance from a populous municipality” is a protective factor for the incidence of the disease. The great variability found for the data that is not explained by the variables used in the model for the incidence of the disease supports the premise that dengue is conditioned by the dynamic interaction among many variables that the study did not approach. The spatial data for infestation by mosquitoes and dengue incidence in the Natural Areas of ES allowed the visualization of the influence of statistically significant variables in the models used in the pattern of introduction and spread of the disease in the state.