Use of geoprocessing to define malaria risk areas and evaluation of the vectorial importance of anopheline mosquitoes (Diptera: Culicidae) in Espírito Santo, Brazil.

In Brazil, introduced malaria occurs from the flat to the sloping hot areas, predominantly outside the Amazon Region, where endemic malaria has occurred in the past. This is a consequence of human migrations to other Brazilian states, including the state of Espírito Santo (ES). The objective of this study was to use geoprocessing to define the areas at risk of introduced malaria transmission and evaluate the vectorial importance of species of anophelines in ES. Anophelines were sampled from 1997-2005 in 297 rural localities identified or not identified as foci of malaria during the last 20 years. The geoclimatic variables temperature, relief and marine influence were obtained from a database of the ES Natural Units. The 14,663 anophelines captured belonged to 22 species. A significant association was found between the occurrence of malaria foci and the presence of hot, low-lying areas or gently undulating to undulating relief. The occurrence of the disease was associated with the presence of Anopheles darlingi and Anopheles aquasalis. Geoprocessing was determined to be a useful tool for defining areas at risk for malaria and vectors in ES.

Environmental Niche Modelling of Phlebotomine Sand Flies and Cutaneous Leishmaniasis Identifies Lutzomyia intermedia as the Main Vector Species in Southeastern Brazil.

Cutaneous leishmaniasis (CL) is caused by a protozoan of the genus Leishmania and is transmitted by sand flies. The state of Espírito Santo (ES), an endemic area in southeast Brazil, has shown a considerably high prevalence in recent decades. Environmental niche modelling (ENM) is a useful tool for predicting potential disease risk. In this study, ENM was applied to sand fly species and CL cases in ES to identify the principal vector and risk areas of the disease. Sand flies were collected in 466 rural localities between 1997 and 2013 using active and passive capture. Insects were identified to the species level, and the localities were georeferenced. Twenty-one bioclimatic variables were selected from WorldClim. Maxent was used to construct models projecting the potential distribution for five Lutzomyia species and CL cases. ENMTools was used to overlap the species and the CL case models. The Kruskal-Wallis test was performed, adopting a 5% significance level. Approximately 250,000 specimens were captured, belonging to 43 species. The area under the curve (AUC) was considered acceptable for all models. The slope was considered relevant to the construction of the models for all the species identified. The overlay test identified Lutzomyia intermedia as the main vector of CL in southeast Brazil. ENM tools enable an analysis of the association among environmental variables, vector distributions and CL cases, which can be used to support epidemiologic and entomological vigilance actions to control the expansion of CL in vulnerable areas.

Use of geoprocessing to define malaria risk areas and evaluation of the vectorial importance of anopheline mosquitoes (Diptera: Culicidae) in Espírito Santo, Brazil

In Brazil, introduced malaria occurs from the flat to the sloping hot areas, predominantly outside the Amazon Region, where endemic malaria has occurred in the past. This is a consequence of human migrations to other Brazilian states, including the state of Espírito Santo (ES). The objective of this study was to use geoprocessing to define the areas at risk of introduced malaria transmission and evaluate the vectorial importance of species of anophelines in ES. Anophelines were sampled from 1997-2005 in 297 rural localities identified or not identified as foci of malaria during the last 20 years. The geoclimatic variables temperature, relief and marine influence were obtained from a database of the ES Natural Units. The 14,663 anophelines captured belonged to 22 species. A significant association was found between the occurrence of malaria foci and the presence of hot, low-lying areas or gently undulating to undulating relief. The occurrence of the disease was associated with the presence of Anopheles darlingi and Anopheles aquasalis. Geoprocessing was determined to be a useful tool for defining areas at risk for malaria and vectors in ES.