The tick Ixodes ricinus (L.) is the most important vector of tick-borne zoonoses in Europe. Apart from factors related to human behavior, tick abundance is a major driver of the incidence of tick-borne diseases in a given area and related data represent critical information for promoting effective public health policies. The present study analyzed the relationship between different environmental factors and tick abundance in order to improve the understanding of I. ricinus autecology and develop spatial predictive models that can be implemented in tick-borne disease prevention strategies. Ticks were sampled in 27 sites over a four-year period and different environmental variables were studied. Five simple models were developed that explain a large part of variation in tick abundance. Precipitation seems to play the most important role, followed by temperature, woodland coverage, and solar radiation. Model equations obtained in this study may enable the spatial interpolation and extension of tick abundance predicted values to sites of the same area, in order to build regional predictive maps. They could also be useful for the validation of large-scale spatial predictive maps.

Investigating the relationship between environmental factors and tick abundance in a small, highly heterogeneous region

DEL FABBRO, Simone;NAZZI, Francesco
2015

Abstract

The tick Ixodes ricinus (L.) is the most important vector of tick-borne zoonoses in Europe. Apart from factors related to human behavior, tick abundance is a major driver of the incidence of tick-borne diseases in a given area and related data represent critical information for promoting effective public health policies. The present study analyzed the relationship between different environmental factors and tick abundance in order to improve the understanding of I. ricinus autecology and develop spatial predictive models that can be implemented in tick-borne disease prevention strategies. Ticks were sampled in 27 sites over a four-year period and different environmental variables were studied. Five simple models were developed that explain a large part of variation in tick abundance. Precipitation seems to play the most important role, followed by temperature, woodland coverage, and solar radiation. Model equations obtained in this study may enable the spatial interpolation and extension of tick abundance predicted values to sites of the same area, in order to build regional predictive maps. They could also be useful for the validation of large-scale spatial predictive maps.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11390/1066735
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