modelagem geoambiental aplicada à favorabilidade de ocorrência de carrapatos vetores de febre maculosa no município de seropédica, rj

Ticks have developed an important role in the transmission of pathogens among wild animals, livestock, pets, and from them to humans. Besides that, ticks are important hosts, vectors and pathogen amplifiers, as they are spread worldwide and have a broad host diversity. The Multiple-criteria Decision Analysis is a mathematical tool that supports the comparison of different scenarios, grounded in many criteria, for the purpose of driving the decision makers to the best choice. The modeling of geographic distribution of species is a relatively recent technique that has become a tool widely applied to ecological studies and species conservation programs. The models are also successfully used to study the association between variables and health problems, to predict and control diseases. The aim of the present study was to analyze the favorability of Amblyomma sculptum occurrence in the municipality of Seropédica, RJ. The modeling was developed using the Geoenvironmental Analysis System SAGA/UFRJ, from Rio de Janeiro Federal University. The method applied is called Analytical Scan and Locational Integration, which is an environmental diagnostic procedure, and three steps were necessary: the variable definition, the multiple-criteria assessment and the environmental signature. To generate the map of favorability of A. sculptum occurrence, we used the Georeferenced Database composed by the following variables: land use and cover, favorability of capybara occurrence, geomorphology and type of soil. The classificatory mapping identified that around 87% of the municipality was favorable or very favorable for A. sculptum occurrence. The low favorability areas were especially related to mining, intense truck traffic, scarce vegetation, high declivity and low favorability of capybara occurrence. The favorable or very favorable areas for tick occurrence were especially related to pasture areas and high or very high favorability of capybara occurrence. The present work may contribute to show that the application of geo-environmental models can help monitoring the occurrence of hosts and