Modelagem na predição de risco de infestação de Aedes aegypti (Diptera, Culicidae) e subsídios governamentais na tomada de decisão para vigil ncia e monitoramento

Abstract

The processes of urbanization and globalization have generated a major problem for public health worldwide, allowing viruses related to vectors such as Aedesa egypti to reemerge violently and become increasingly widespread, causing death. Therefore, actions that focus on the planning and control of vector infestation based on risk prevention models with reliable statistical results have become necessary so that priority control can be developed. In the present study, we used a dataset from the LIRAa and the government investment to control Ae. Aegypti referring to 281 Brazilian municipalities. The data from the LIRAa were obtained from the Ministry of Health and all data were limited to municipalities that had continuous data from 2011 to 2015 so that there was a temporal logic in the analyzes. The main goal of this study was to build prediction models for the risk of Ae. aegypti infestation levels together with data obtained from the LIRAa of the years 2011 and 2015. Hence, potential risk models were constructed using the MaxEnt software, based on the geographical coordinates of the municipalities and from climatic data from all over the country to indicate the locations with the highest levels of vector infestation risk. In addition, the final per capita investment values per year were correlated with the LIRAa values of each year in order to analyze whether the investments made had an effect on infestation levels. The results suggest that there was no correlation between the government efforts and the LIRAa of the years sampled, with epidemiological risk models indicating that the variation in infestation levels is probably due to environmental and socioeconomic factors.