Predicting the spatio-temporal risk of human tick-borne encephalitis (TBE) in Europe by combining hazard and exposure drivers

This pre-released repository contains all data, code, and model outputs used in the study:"Predicting the spatio-temporal risk of human tick-borne encephalitis (TBE) in Europe by combining hazard and exposure drivers." The materials provided allow for full reproducibility of the analytical workflow described in the manuscript. Due to data-sharing restrictions, the original epidemiological dataset containing human TBE case data cannot be shared publicly. However, a synthetic ("dummy") version of the human case variable is included to ensure that all scripts can be executed and the modeling pipeline reproduced. Contents: 📃 R scripts for model training, simulation, and figure generation 📁 Data/: Covariate datasets and synthetic ("dummy") TBE presence/absence data at NUTS-3 and municipal level 📁 Results/: Fitted model and predicted probabilities of TBE occurrence (2017–2025) at NUTS-3 and municipal levels 📁 Figures/: Figures generated from the results 📁 Folds/: Model folds used for cross-validation All data are provided in .RData format. Detailed README files are included in each folder to guide users through the structure and content. Important Disclaimer: The dummy datasets included in this repository are for illustrative and computational purposes only. They do not reflect the true geographic distribution of TBE and are not intended for analysis or interpretation.   This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 874850 and is catalogued as MOOD 081. The contents of this publication are the sole responsibility of the authors and don't necessarily reflect the views of the European Commission.