Spatial and seasonal determinants of Lyme borreliosis incidence in France, 2016 to 2021

Abstract

Background Lyme borreliosis (LB) is the most widespread hard tick-borne zoonosis in the northern hemisphere. Existing studies in Europe have focused mainly on acarological risk assessment, with few investigations exploring human LB occurrence. Aim We explored the determinants of spatial and seasonal LB variations in France from 2016 to 2021 by integrating environmental, animal, meteorological and anthropogenic factors, and then mapped seasonal LB risk predictions. Methods We fitted 2016–19 LB national surveillance data to a two-part spatio-temporal statistical model. Spatial and temporal random effects were specified using a Besag-York-Mollie model and a seasonal model, respectively. Coefficients were estimated in a Bayesian framework using integrated nested Laplace approximation. Data from 2020–21 were used for model validation. Results A high vegetation index (≥ 0.6) was positively associated with seasonal LB presence, while the index of deer presence (> 60%), mild soil temperature (15–22 °C), moderate air saturation deficit (1.5–5 mmHg) and higher tick bite frequency were associated with increased incidence. Prediction maps show a higher risk of LB in spring and summer (April–September), with higher incidence in parts of eastern, midwestern and south-western France. Conclusion We present a national level spatial assessment of seasonal LB occurrence in Europe, disentangling factors associated with the presence and increased incidence of LB. Our findings yield quantitative evidence for national public health agencies to plan targeted prevention campaigns to reduce LB burden, enhance surveillance and identify further data needs. This approach can be tested in other LB endemic areas.

Species distribution modeling of the castor bean tick,Ixodes ricinus(Linnaeus, 1758), under current and future climates, with a special focus on Ukraine and Latvia

“…We assume this can be accomplished by correlating the obtained habitat suitability values of each SDM with reported incidence of Lyme disease and hypothesizing that a closer correlation would point towards a model that fits our needs the most. Existing studies in Europe mainly focus on acarological risk assessment, with very limited investigations exploring Lyme disease occurrence in human [79]. As an example, incidences of Lyme disease in Ukraine are scarcely reported so that proper statistical analyses cannot be achieved.…”