Bioclimatic modelling of the spread of the West Nile virus in Europe, with a special focus on Ukraine

West Nile virus (WNV) is a re-emerging zoonotic pathogen transmitted by mosquitoes and causes fever and encephalitis in humans, equines, and birds.While all WNV lineages can cause human illness, the lineage WNV2 has gained particular attention in Europe due to its rapid spread and potential for causing severe disease, with large outbreaks happening in summer months.While WNV is not as prevalent in Ukraine as in some other regions of Europe, outbreaks do occur periodically. This is becoming an alarming trend. In this study we focused on the ability of bioclimatic predictors to envisage WNV outbreaks in Europe, making a special emphasis on Ukraine. For this purpose we employ a machine learning methodology for drawing predictions and the SHAP framework from XAI (i.e., eXplainable artificial intelligence) to rank and uncover the most influential WNV drivers.In terms of bioclimatic predictors, the most important for SDM constructions at the European scale was the mean daily air temperature of the coldest quarter and temperature seasonality for Ukraine. Our model suggests that under an impending health threat are areas in the west (excluding the Carpathian highlands) and south of Ukraine.