Evidence map›Paper›PMID 37022210›Full record

ArticleEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin2023

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

Wen Fu, Camille Bonnet, Alexandra Septfons, Julie Figoni, Jonas Durand, Pascale Frey-Klett, Denis Rustand, Benoît Jaulhac, Raphaëlle Métras

Open access · diamondAbstract read
In one paragraph

Article in Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.4field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 12 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 5 institutions in 3 countries.

Wen FuSorbonne Université, INSERM, Institut Pierre Louis d'Épidémiologie et de Santé Publique, Paris, France.
Camille BonnetSorbonne Université, INSERM, Institut Pierre Louis d'Épidémiologie et de Santé Publique, Paris, France.
Alexandra SeptfonsSanté publique France, Saint-Maurice, France.
Julie FigoniSanté publique France, Saint-Maurice, France.
Jonas DurandLaboratoire Tous Chercheurs, Université de Lorraine, INRAE, UMR 1136 Interactions Arbres-Microorganismes, Nancy, France.
Pascale Frey-KlettLaboratoire Tous Chercheurs, Université de Lorraine, INRAE, UMR 1136 Interactions Arbres-Microorganismes, Nancy, France.
Denis RustandStatistics Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.
Benoît JaulhacFrench National Reference Center for Borrelia, Hôpitaux Universitaires de Strasbourg, Strasbourg, France.
Raphaëlle MétrasSorbonne Université, INSERM, Institut Pierre Louis d'Épidémiologie et de Santé Publique, Paris, France.
Inserm · FRInstitut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement · FRSanté Publique France · FRHôpitaux Universitaires de Strasbourg · FRKing Abdullah University of Science and Technology · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BackgroundLyme 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.AimWe 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.MethodsWe 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.ResultsA 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.ConclusionWe 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.

Indexed as

DeerLyme DiseaseAnimalsBayes TheoremFranceHumansIncidenceSeasonsBayesian inferenceLyme borreliosisrisk factorsspatio-temporal epidemiologytick-borne diseases

Identifiers

PMID37022210
PMCPMC10283463
OpenAlexW4362657580

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.