Estimation of the dispersal distances of an aphid-borne virus in a patchy landscape.

Characterising the spatio-temporal dynamics of pathogens in natura is key to ensuring their efficient prevention and control. However, it is notoriously difficult to estimate dispersal parameters at scales that are relevant to real epidemics. Epidemiological surveys can provide informative data, but...

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Main Authors: David R J Pleydell, Samuel Soubeyrand, Sylvie Dallot, Gérard Labonne, Joël Chadœuf, Emmanuel Jacquot, Gaël Thébaud
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2018-04-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.1006085
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spelling doaj-d49249a3839e4e23b9d404f188db20272021-08-12T04:31:46ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582018-04-01144e100608510.1371/journal.pcbi.1006085Estimation of the dispersal distances of an aphid-borne virus in a patchy landscape.David R J PleydellSamuel SoubeyrandSylvie DallotGérard LabonneJoël ChadœufEmmanuel JacquotGaël ThébaudCharacterising the spatio-temporal dynamics of pathogens in natura is key to ensuring their efficient prevention and control. However, it is notoriously difficult to estimate dispersal parameters at scales that are relevant to real epidemics. Epidemiological surveys can provide informative data, but parameter estimation can be hampered when the timing of the epidemiological events is uncertain, and in the presence of interactions between disease spread, surveillance, and control. Further complications arise from imperfect detection of disease and from the huge number of data on individual hosts arising from landscape-level surveys. Here, we present a Bayesian framework that overcomes these barriers by integrating over associated uncertainties in a model explicitly combining the processes of disease dispersal, surveillance and control. Using a novel computationally efficient approach to account for patch geometry, we demonstrate that disease dispersal distances can be estimated accurately in a patchy (i.e. fragmented) landscape when disease control is ongoing. Applying this model to data for an aphid-borne virus (Plum pox virus) surveyed for 15 years in 605 orchards, we obtain the first estimate of the distribution of flight distances of infectious aphids at the landscape scale. About 50% of aphid flights terminate beyond 90 m, which implies that most infectious aphids leaving a tree land outside the bounds of a 1-ha orchard. Moreover, long-distance flights are not rare-10% of flights exceed 1 km. By their impact on our quantitative understanding of winged aphid dispersal, these results can inform the design of management strategies for plant viruses, which are mainly aphid-borne.https://doi.org/10.1371/journal.pcbi.1006085
collection DOAJ
language English
format Article
sources DOAJ
author David R J Pleydell
Samuel Soubeyrand
Sylvie Dallot
Gérard Labonne
Joël Chadœuf
Emmanuel Jacquot
Gaël Thébaud
spellingShingle David R J Pleydell
Samuel Soubeyrand
Sylvie Dallot
Gérard Labonne
Joël Chadœuf
Emmanuel Jacquot
Gaël Thébaud
Estimation of the dispersal distances of an aphid-borne virus in a patchy landscape.
PLoS Computational Biology
author_facet David R J Pleydell
Samuel Soubeyrand
Sylvie Dallot
Gérard Labonne
Joël Chadœuf
Emmanuel Jacquot
Gaël Thébaud
author_sort David R J Pleydell
title Estimation of the dispersal distances of an aphid-borne virus in a patchy landscape.
title_short Estimation of the dispersal distances of an aphid-borne virus in a patchy landscape.
title_full Estimation of the dispersal distances of an aphid-borne virus in a patchy landscape.
title_fullStr Estimation of the dispersal distances of an aphid-borne virus in a patchy landscape.
title_full_unstemmed Estimation of the dispersal distances of an aphid-borne virus in a patchy landscape.
title_sort estimation of the dispersal distances of an aphid-borne virus in a patchy landscape.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2018-04-01
description Characterising the spatio-temporal dynamics of pathogens in natura is key to ensuring their efficient prevention and control. However, it is notoriously difficult to estimate dispersal parameters at scales that are relevant to real epidemics. Epidemiological surveys can provide informative data, but parameter estimation can be hampered when the timing of the epidemiological events is uncertain, and in the presence of interactions between disease spread, surveillance, and control. Further complications arise from imperfect detection of disease and from the huge number of data on individual hosts arising from landscape-level surveys. Here, we present a Bayesian framework that overcomes these barriers by integrating over associated uncertainties in a model explicitly combining the processes of disease dispersal, surveillance and control. Using a novel computationally efficient approach to account for patch geometry, we demonstrate that disease dispersal distances can be estimated accurately in a patchy (i.e. fragmented) landscape when disease control is ongoing. Applying this model to data for an aphid-borne virus (Plum pox virus) surveyed for 15 years in 605 orchards, we obtain the first estimate of the distribution of flight distances of infectious aphids at the landscape scale. About 50% of aphid flights terminate beyond 90 m, which implies that most infectious aphids leaving a tree land outside the bounds of a 1-ha orchard. Moreover, long-distance flights are not rare-10% of flights exceed 1 km. By their impact on our quantitative understanding of winged aphid dispersal, these results can inform the design of management strategies for plant viruses, which are mainly aphid-borne.
url https://doi.org/10.1371/journal.pcbi.1006085
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