Publication date: 27/10/2020

Namesort descending Role

Examining board:

Namesort descending Role
BLIMA FUX Advisor *

Summary: Lutzomyia longipalpis is the main vector of visceral leishmaniasis (VL) in Brazil. In the state of Espírito Santo (ES), the first cases of the disease were diagnosed in two municipalities in the late 1960s. Today, ten municipalities are considered endemic for the disease. Considering the current area of occurrence of VL in ES, it is believed that the endemic migrated from the state of Minas Gerais, through the Rio Doce valley, WHERE the vector finds a favorable environment for its development. Spatial analysis has been widely used to elucidate the mechanisms of disease dispersion, in order to predict their progress to new areas and to propose control measures. Geographic information systems play this role well, enabling the analysis of the relationships between environment and health-related events. Our objective was to build an ecological niche model for L. longipalpis in ES, predicting the areas with possible insect occurrence, thus alerting future installation of VL, as well as directing resources to priority areas. Climate variables were listed from the WorldClim database, while geographic variables were from INPE and Geobases. The presence data of the transmitting species are the result of more than 30 years of entomological research in the state. We use the Arcgis program (Version 10.3.1) for insertion of the selected variables and the MaxEnt algorithm for ecological niche modeling (ENM). The area under ROC curve (AUC) was greater than 0.9 indicating that the generated model was excellent. Among the variables studied, the rocky outcrop was the one that most contributed to the generation of the model, followed by thermal seasonality, altitude and annual thermal oscillation. The vector L. longipalpis is found so far in 18 municipalities in Espírito Santo. The MNE allows a better understanding of the geographic distribution, both of the vector Lutzomyia longipalpis, and of the LVA. If this distribution is better understood, more effective surveillance and control actions can be subsidized, covering areas with a higher probability of disease or vector transmission

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