Geospatial data mining in volunteer data : how natural conditions might increase the risk of tick bites and Lyme disease?

There is evidence of an increase of tick bites and Lyme disease in the Netherlands since 1994. Scientists of different disciplines have demonstrated the tight bond between natural conditions and the abundance of ticks in forests. However, traditional statistical models are too restrictive to model tick dynamics, as they require a significant number of predictors. In this work, we combine a tick bite dataset collected by citizens between 2006-2012, satellite-derived vegetation indices and weather data to advance our understanding of the impact of environmental conditions on tick bites reports and assess the value of volunteered information to model tick bites dynamics. This data was analysed using clustering and frequent pattern mining algorithms. Results show that this approach seems promising to identify environmental conditions that may be linked to a higher risk to get a tick bite.