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Efficient use of sentinel sites: detection of invasive honeybee pests and diseases in the UK

Sentinel sites, where problems can be identified early or investigated in detail, form an important part of planning for exotic disease outbreaks in humans, livestock and plants. Key questions are: how many sentinels are required, where should they be positioned and how effective are they at rapidly...

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Detalles Bibliográficos
Autores principales: Keeling, Matt J., Datta, Samik, Franklin, Daniel N., Flatman, Ivor, Wattam, Andy, Brown, Mike, Budge, Giles E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5414905/
https://www.ncbi.nlm.nih.gov/pubmed/28446703
http://dx.doi.org/10.1098/rsif.2016.0908
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author Keeling, Matt J.
Datta, Samik
Franklin, Daniel N.
Flatman, Ivor
Wattam, Andy
Brown, Mike
Budge, Giles E.
author_facet Keeling, Matt J.
Datta, Samik
Franklin, Daniel N.
Flatman, Ivor
Wattam, Andy
Brown, Mike
Budge, Giles E.
author_sort Keeling, Matt J.
collection PubMed
description Sentinel sites, where problems can be identified early or investigated in detail, form an important part of planning for exotic disease outbreaks in humans, livestock and plants. Key questions are: how many sentinels are required, where should they be positioned and how effective are they at rapidly identifying new invasions? The sentinel apiary system for invasive honeybee pests and diseases illustrates the costs and benefits of such approaches. Here, we address these issues with two mathematical modelling approaches. The first approach is generic and uses probabilistic arguments to calculate the average number of affected sites when an outbreak is first detected, providing rapid and general insights that we have applied to a range of infectious diseases. The second approach uses a computationally intensive, stochastic, spatial model to simulate multiple outbreaks and to determine appropriate sentinel locations for UK apiaries. Both models quantify the anticipated increase in success of sentinel sites as their number increases and as non-sentinel sites become worse at detection; however, unexpectedly sentinels perform relatively better for faster growing outbreaks. Additionally, the spatial model allows us to quantify the substantial role that carefully positioned sentinels can play in the rapid detection of exotic invasions.
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spelling pubmed-54149052017-05-08 Efficient use of sentinel sites: detection of invasive honeybee pests and diseases in the UK Keeling, Matt J. Datta, Samik Franklin, Daniel N. Flatman, Ivor Wattam, Andy Brown, Mike Budge, Giles E. J R Soc Interface Life Sciences–Mathematics interface Sentinel sites, where problems can be identified early or investigated in detail, form an important part of planning for exotic disease outbreaks in humans, livestock and plants. Key questions are: how many sentinels are required, where should they be positioned and how effective are they at rapidly identifying new invasions? The sentinel apiary system for invasive honeybee pests and diseases illustrates the costs and benefits of such approaches. Here, we address these issues with two mathematical modelling approaches. The first approach is generic and uses probabilistic arguments to calculate the average number of affected sites when an outbreak is first detected, providing rapid and general insights that we have applied to a range of infectious diseases. The second approach uses a computationally intensive, stochastic, spatial model to simulate multiple outbreaks and to determine appropriate sentinel locations for UK apiaries. Both models quantify the anticipated increase in success of sentinel sites as their number increases and as non-sentinel sites become worse at detection; however, unexpectedly sentinels perform relatively better for faster growing outbreaks. Additionally, the spatial model allows us to quantify the substantial role that carefully positioned sentinels can play in the rapid detection of exotic invasions. The Royal Society 2017-04 2017-04-26 /pmc/articles/PMC5414905/ /pubmed/28446703 http://dx.doi.org/10.1098/rsif.2016.0908 Text en © 2017 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Life Sciences–Mathematics interface
Keeling, Matt J.
Datta, Samik
Franklin, Daniel N.
Flatman, Ivor
Wattam, Andy
Brown, Mike
Budge, Giles E.
Efficient use of sentinel sites: detection of invasive honeybee pests and diseases in the UK
title Efficient use of sentinel sites: detection of invasive honeybee pests and diseases in the UK
title_full Efficient use of sentinel sites: detection of invasive honeybee pests and diseases in the UK
title_fullStr Efficient use of sentinel sites: detection of invasive honeybee pests and diseases in the UK
title_full_unstemmed Efficient use of sentinel sites: detection of invasive honeybee pests and diseases in the UK
title_short Efficient use of sentinel sites: detection of invasive honeybee pests and diseases in the UK
title_sort efficient use of sentinel sites: detection of invasive honeybee pests and diseases in the uk
topic Life Sciences–Mathematics interface
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5414905/
https://www.ncbi.nlm.nih.gov/pubmed/28446703
http://dx.doi.org/10.1098/rsif.2016.0908
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