Modelling the impact of climate and the environment on the spatiotemporal dynamics of Lyme borreliosis in Germany

TL;DR

This study models how climate and environmental factors influence the spread of Lyme borreliosis in Germany, identifying key conditions that increase disease risk.

Contribution

The study introduces a Bayesian modeling framework to assess delayed and nonlinear climate-environment-Lyme disease associations in Germany.

Findings

Maximum temperatures between 10.5°C and 26.3°C and high humidity are linked to increased Lyme borreliosis risk.

Wet conditions over three months and deer-populated areas are associated with higher tick survival and disease transmission.

Lyme risk is increasing in northern German states, including those without mandatory case reporting.

Abstract

Lyme borreliosis (LB) is a predominant vector-borne disease in Europe, with Germany reporting endemic circulation for at least the past two decades. Climatic and environmental conditions are key drivers of tick activity, and human exposure to tick bites. Understanding the climatic and environmental factors driving LB dynamics can help devise decision-support tools to guide interventions and adaptation strategies.

Using a Bayesian modelling framework, we assessed the delayed and nonlinear associations between climate variation and land use change and monthly LB case counts from the German national notification system at a district level from 2009 to 2022. We evaluated the predictive performance of our model and then predicted risk trends in states without mandatory notification. We then used the fitted risk function for maximum temperature to assess long-term trends in relative risk since the 1950s.

Our analyses revealed that climate and environmental factors are positively associated with LB cases reported to the national notification system. Maximum temperature between 10.5 °C and 26.3 °C two to four months prior, relative humidity levels exceeding 78.8% six months prior, and exceptionally wet conditions accumulated over three months, lagged by one month, were associated with an increased risk of LB. The effect of relative humidity was only relevant in areas suitable for deer population, potentially linked to tick survival. Predictions from our model identified significant increasing trends in Schleswig–Holstein, Hamburg, and Lower Saxony, three states without mandatory case notification. We also observed an increasing trend in maximum-temperature related LB relative risk in all Federal States, with the largest percentage change in the period 2013–2022 in northern districts, compared to 1951–1970.

Our study underscores the role of climatic variables as potential drivers of LB risk in Germany. We identified optimal conditions that may be related to human exposure and tick survival and detected long-term upward trends nationwide, including in areas without mandatory notification. This decision-support modelling framework emphasises the added value of expanding LB surveillance in Germany and across Europe to address the emerging risk of tick-borne infectious diseases.

10.13039/501100009318Helmholtz Association, Helmholtz Climate Initiative, 10.13039/100010269Wellcome Trust, 10.13039/501100000288Royal Society, and 10.13039/100018693Horizon Europe.

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