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

Author:

Fu Wen1ORCID,Bonnet Camille1ORCID,Septfons Alexandra2ORCID,Figoni Julie2ORCID,Durand Jonas3ORCID,Frey-Klett Pascale3,Rustand Denis4ORCID,Jaulhac Benoît56ORCID,Métras Raphaëlle781ORCID

Affiliation:

1. Sorbonne Université, INSERM, Institut Pierre Louis d’Épidémiologie et de Santé Publique, Paris, France

2. Santé publique France, Saint-Maurice, France

3. Laboratoire Tous Chercheurs, Université de Lorraine, INRAE, UMR 1136 Interactions Arbres-Microorganismes, Nancy, France

4. Statistics Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia

5. Institut de Bactériologie, Fédération de Médecine Translationnelle de Strasbourg, University of Strasbourg,ITI InnoVec, Strasbourg, France

6. French National Reference Center for Borrelia, Hôpitaux Universitaires de Strasbourg, Strasbourg, France

7. Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom

8. Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom

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.

Publisher

European Centre for Disease Control and Prevention (ECDC)

Subject

Virology,Public Health, Environmental and Occupational Health,Epidemiology

Reference48 articles.

1. Lyme borreliosis.;Stanek;Lancet,2012

2. An estimate of Lyme borreliosis incidence in Western Europe.;Sykes;J Public Health (Oxf),2017

3. The evolving story of Borrelia burgdorferi sensu lato transmission in Europe.;Steinbrink;Parasitol Res,2022

4. Première contribution à l’étude écologique d’Ixodes ricinus (Linné, 1758) (Acarina, Ixodoidea) dans le Sud-Est de la France. [Ecological study of Ixodes ricinus (Linné, 1758) (Acarina, Ixodoides) in southeastern France.];Gilot;Acta Trop,1975

5. L’analyse de la végétation appliquée á la détection des populations de tiques exophiles dans le sud-est de la France: l’exemple d’lxodes ricinus (Linné 1758) (acarina, Ixodoidea). [Vegetation analysis used for the detection of exophile tick populations in the south-east of France: the example Ixodes ricinus (Linne 1758) (acarina, ixodoidea)].;Gilot;Acta Trop,1975

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