Spatial and temporal distribution patterns of tick-borne diseases (Tick-borne Encephalitis and Lyme Borreliosis) in Germany

Background: In the face of ongoing climate warming, vector-borne diseases are expected to increase in Europe, including tick-borne diseases (TBD). The most abundant tick-borne diseases in Germany are Tick-Borne Encephalitis (TBE) and Lyme Borreliosis (LB), with Ixodes ricinus as the main vector. Methods: In this study, we display and compare the spatial and temporal patterns of reported cases of human TBE and LB in relation to some associated factors. The comparison may help with the interpretation of observed spatial and temporal patterns. Results: The spatial patterns of reported TBE cases show a clear and consistent pattern over the years, with many cases in the south and only few and isolated cases in the north of Germany. The identification of spatial patterns of LB disease cases is more difficult due to the different reporting practices in the individual federal states. Temporal patterns strongly fluctuate between years, and are relatively synchronized between both diseases, suggesting common driving factors. Based on our results we found no evidence that weather conditions affect the prevalence of both diseases. Both diseases show a gender bias with LB bing more commonly diagnosed in females, contrary to TBE being more commonly diagnosed in males. Conclusion: For a further investigation of of the underlying driving factors and their interrelations, longer time series as well as standardised reporting and surveillance system would be required.

Automated summary

The spatial patterns of reported TBE cases in Germany show a clear pattern with many cases in the south and fewer cases in the north. Temporal patterns fluctuate strongly between years and are relatively synchronized between TBE and LB, with no evidence of weather conditions affecting disease prevalence. Gender bias was observed, with LB more commonly diagnosed in females and TBE more commonly diagnosed in males. Longer time series and standardized reporting are needed for further investigation of underlying driving factors and their interrelations.