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Bayesian inference for spatio-temporal stochastic transmission of plant disease in the presence of roguing: A case study to characterise the dispersal of Flavescence dorée

hal.structure.identifierSanté et agroécologie du vignoble [UMR SAVE]
dc.contributor.authorADRAKEY, Hola
hal.structure.identifierMaxwell Institute for Mathematical Sciences
dc.contributor.authorGIBSON, Gavin
hal.structure.identifierBiologie du fruit et pathologie [BFP]
dc.contributor.authorEVEILLARD, Sandrine
hal.structure.identifierBiologie du fruit et pathologie [BFP]
dc.contributor.authorMALEMBIC-MAHER, Sylvie
hal.structure.identifierSanté et agroécologie du vignoble [UMR SAVE]
dc.contributor.authorFABRE, Frederic
dc.date.accessioned2023-11-20T17:17:31Z
dc.date.available2023-11-20T17:17:31Z
dc.date.issued2023-09-01
dc.identifier.issn1553-734X
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/185289
dc.description.abstractEnEstimating the distance at which pathogens disperse from one season to the next is crucial for designing efficient control strategies for invasive plant pathogens and a major milestone in the reduction of pesticide use in agriculture. However, we still lack such estimates for many diseases, especially for insect-vectored pathogens, such as Flavescence dorée (FD). FD is a quarantine disease threatening European vineyards. Its management is based on mandatory insecticide treatments and the removal of infected plants identified during annual surveys. This paper introduces a general statistical framework to model the epidemiological dynamics of FD in a mechanistic manner that can take into account missing hosts in surveyed fields (resulting from infected plant removals). We parameterized the model using Markov chain Monte Carlo (MCMC) and data augmentation from surveillance data gathered in Bordeaux vineyards. The data mainly consist of two snapshot maps of the infectious status of all the plants in three adjacent fields during two consecutive years. We demonstrate that heavy-tailed dispersal kernels best fit the spread of FD and that on average, 50% (resp. 80%) of new infection occurs within 10.5 m (resp. 22.2 m) of the source plant. These values are in agreement with estimates of the flying capacity of Scaphoideus titanus , the leafhopper vector of FD, reported in the literature using mark–capture techniques. Simulations of simple removal scenarios using the fitted model suggest that cryptic infection hampered FD management. Future efforts should explore whether strategies relying on reactive host removal can improve FD management.
dc.language.isoen
dc.publisherPublic Library of Science
dc.rights.urihttp://creativecommons.org/licenses/by/
dc.subjectinsecte vecteur
dc.subjectAgent pathogène
dc.subjectFlavescence Dorée
dc.subjectmollicute
dc.subjectvignoble
dc.subjectScaphoideus Titanus
dc.subject.enplant pathology
dc.subject.enphytoplasma
dc.subject.enepidemiology
dc.subject.enplant pathogens
dc.title.enBayesian inference for spatio-temporal stochastic transmission of plant disease in the presence of roguing: A case study to characterise the dispersal of Flavescence dorée
dc.typeArticle de revue
dc.identifier.doi10.1371/journal.pcbi.1011399
dc.subject.halSciences du Vivant [q-bio]
dc.subject.halSciences du Vivant [q-bio]/Biologie végétale/Phytopathologie et phytopharmacie
bordeaux.journalPLoS Computational Biology
bordeaux.pagee1011399
bordeaux.volume19
bordeaux.hal.laboratoriesBiologie du Fruit & Pathologie (BFP) - UMR 1332*
bordeaux.issue9
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-04216679
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-04216679v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=PLoS%20Computational%20Biology&rft.date=2023-09-01&rft.volume=19&rft.issue=9&rft.spage=e1011399&rft.epage=e1011399&rft.eissn=1553-734X&rft.issn=1553-734X&rft.au=ADRAKEY,%20Hola&GIBSON,%20Gavin&EVEILLARD,%20Sandrine&MALEMBIC-MAHER,%20Sylvie&FABRE,%20Frederic&rft.genre=article


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