Background The geographic range, seasonality, and incidence of many infectious diseases might change with climate change. Yet, most models of these eff ects have not been able to account for the exacerbating or mitigating eff ects of socioeconomic variables. Vulnerability is understood to be the propensity to be adversely aff ected by a given cause. We assessed vulnerabilities and how these aff ect the relations between infectious disease transmission and climate change. Methods We developed vulnerability indices at the subnational level for 2035, and 2055. We assessed various datasets for their inclusion in a conceptual framework of vulnerability (consisting of impact and adaptive capacity). We plotted the projected change in absolute precipitation and temperature for European regions and used it as a proxy for change in temperature-sensitive infectious disease incidence. We used climate change projections of European-wide monthly means for daily temperature (T min and T max in °C) and daily precipitation (in mm) for 2035 and 2055, to map possible changes in infectious disease risk. These projections were based on a multimodel ensemble with three emission scenarios (A1b, A2, B1) and four earth system models (ECHAM5, MIROC3, CNRM, CSIRO3) and downscaled to 1 km resolution. We used a composite adaptive capacity indicator to assess vulnerability on the basis of regional adaptive capacity index developed by the ESPON project. Final vulnerability indices combined the impact and adaptive capacity indices, plotted via ArcGIS to EU regions for 2035 and 2055 and ranked into quintiles. We assessed the key factors driving the impact and vulnerability indices with a Spearman rank correlation test.