By Jacob Beeuwkes
Abstract:
Lyme disease is an infectious disease in human that is caused by the spirochete Borrelia burgdorferi. The European sheep tick (Ixodes ricinus) is vector of this bacterium and can transmit it during blood meals. The density of ticks in an area can indicate the spatial risk of obtaining Lyme disease. Therefore data from 6 different tick sampling studies, at different locations broadly distributed over the Netherlands, was combined and spatially analyzed. Early summer densities of the nymphal stage were found to be associated with roe deer density, land use, April NDVI and climatic variables. A map predicting the nymphal density was made based on associative variables. A part of the dataset was used to test the predictive capability of the model, which turned out to be 71%. Predictive maps of the risk to obtain Lyme disease are vital because they may help people to take preventative measures at the right place and time. Therefore it is suggested that efforts should be taken in developing web-based GIS that enables spatio-temporal mapping of this risk in the Netherlands, to inform a broad public in a convenient way.