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231225s2018 xx |||||o 00| ||eng c |
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|a 10.1111/nph.15177
|2 doi
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|a pubmed24n1596.xml
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|a DE-627
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|e rakwb
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|a eng
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|a Soubeyrand, Samuel
|e verfasserin
|4 aut
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|a Inferring pathogen dynamics from temporal count data
|b the emergence of Xylella fastidiosa in France is probably not recent
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|c 2018
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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|a Date Completed 20.09.2019
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|a Date Revised 10.11.2024
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.
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|a Unravelling the ecological structure of emerging plant pathogens persisting in multi-host systems is challenging. In such systems, observations are often heterogeneous with respect to time, space and host species, and may lead to biases of perception. The biased perception of pathogen ecology may be exacerbated by hidden fractions of the whole host population, which may act as infection reservoirs. We designed a mechanistic-statistical approach to help understand the ecology of emerging pathogens by filtering out some biases of perception. This approach, based on SIR (Susceptible-Infected-Removed) models and a Bayesian framework, disentangles epidemiological and observational processes underlying temporal counting data. We applied our approach to French surveillance data on Xylella fastidiosa, a multi-host pathogenic bacterium recently discovered in Corsica, France. A model selection led to two diverging scenarios: one scenario without a hidden compartment and an introduction around 2001, and the other with a hidden compartment and an introduction around 1985. Thus, Xylella fastidiosa was probably introduced into Corsica much earlier than its discovery, and its control could be arduous under the hidden compartment scenario. From a methodological perspective, our approach provides insights into the dynamics of emerging plant pathogens and, in particular, the potential existence of infection reservoirs
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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|a Bayesian inference
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|a emerging plant pathogen
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|a infection reservoir
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|a introduction date
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|a mechanistic-statistical model
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|a multi-host pathogen
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|a plant-pathogen interaction
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|a surveillance data
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|a de Jerphanion, Pauline
|e verfasserin
|4 aut
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|a Martin, Olivier
|e verfasserin
|4 aut
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|a Saussac, Mathilde
|e verfasserin
|4 aut
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|a Manceau, Charles
|e verfasserin
|4 aut
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|a Hendrikx, Pascal
|e verfasserin
|4 aut
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|a Lannou, Christian
|e verfasserin
|4 aut
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|i Enthalten in
|t The New phytologist
|d 1979
|g 219(2018), 2 vom: 01. Juli, Seite 824-836
|w (DE-627)NLM09818248X
|x 1469-8137
|7 nnns
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|g volume:219
|g year:2018
|g number:2
|g day:01
|g month:07
|g pages:824-836
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|u http://dx.doi.org/10.1111/nph.15177
|3 Volltext
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