Fig. 1

Workflow for mapping tick attachment to humans. Data on tick attachment to humans were collected through the Tick Prevention app. These data records served as training data for a model utilizing the software extension spatialMaxent, alongside background points derived from environmental variables. These environmental variables encompassed four temporal resolutions: static variables (e.g., digital height model), yearly data (e.g., population density), seasonal data (e.g., optical remote sensing data), and monthly data (e.g., weather data). During model creation, a variable selection process is initially conducted, where the most significant variables are automatically identified by the model. Subsequently, the other model parameters are tuned. The final model is trained with the best-performing parameters and variables. The performance of the model was assessed using artificial absence points derived from areas with minimal tick occurrence probability, such as lakes. Subsequently, 84 maps depicting tick attachment to humans from January 2015 to December 2021 were generated at a spatial resolution of 100 m