Evidence map›Paper›PMID 28446703›Full record

ArticleJournal of the Royal Society, Interface2017

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

Matt J Keeling, Samik Datta, Daniel N Franklin, Ivor Flatman, Andy Wattam, Mike Brown, Giles E Budge

Open access · hybridAbstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
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

7 authors at 3 institutions in 1 country.

Matt J KeelingZeeman Institute: SBIDER, University of Warwick, Coventry CV4 7AL, UK m.j.keeling@warwick.ac.uk.ORCID 0000-0003-4639-4765
Samik DattaZeeman Institute: SBIDER, University of Warwick, Coventry CV4 7AL, UK.
Daniel N FranklinZeeman Institute: SBIDER, University of Warwick, Coventry CV4 7AL, UK.
Ivor FlatmanAnimal and Plant Health Agency, Sand Hutton, York YO41 1LZ, UK.
Andy WattamAnimal and Plant Health Agency, Sand Hutton, York YO41 1LZ, UK.
Mike BrownAnimal and Plant Health Agency, Sand Hutton, York YO41 1LZ, UK.
Giles E BudgeFera, Sand Hutton, York YO41 1LZ, UK giles.budge@newcastle.ac.uk.ORCID 0000-0001-6175-2095
Animal and Plant Health Agency · GBUniversity of Warwick · GBFera Science (United Kingdom) · GB

Funding

Biotechnology and Biological Sciences Research Council BB/I000615/1Biotechnology and Biological Sciences Research Council BB/I000801/1
6 · The paper itself

Abstract

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.

Indexed as

BeesModels, StatisticalSentinel SurveillanceSurvival AnalysisAnimal DiseasesAnimalsComputer SimulationDisease OutbreaksIncidenceReproducibility of ResultsRisk AssessmentSensitivity and SpecificitySpatio-Temporal AnalysisUnited Kingdomeradicationfoulbroodinvasionpathogensmall hive beetleTropilaelaps

Identifiers

PMID28446703
PMCPMC5414905
OpenAlexW2608159523

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.