Evidence map›Paper›PMID 24670977›Full record

ArticlePloS one2014

The impact of movements and animal density on continental scale cattle disease outbreaks in the United States.

Michael G Buhnerkempe, Michael J Tildesley, Tom Lindström, Daniel A Grear, Katie Portacci, Ryan S Miller, Jason E Lombard, Marleen Werkman, Matt J Keeling, Uno Wennergren and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 2 pooled it
12.6field-weighted citation impact, top 1% 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

36 citing papers in PubMed, 2 syntheses or guidelines pooled it, 76 citations in OpenAlex.

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  8. The veterinary quarterly · 2024
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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

11 authors at 5 institutions in 3 countries.

Michael G BuhnerkempeDepartment of Biology, Colorado State University, Fort Collins, Colorado, United States of America.
Michael J TildesleyCenter for Complexity Science, Mathematics Institute, University of Warwick, Coventry, United Kingdom.
Tom LindströmDepartment of Physics, Chemistry, and Biology, Linköping University, Linköping, Sweden.
Daniel A GrearDepartment of Biology, Colorado State University, Fort Collins, Colorado, United States of America.
Katie PortacciUnited States Department of Agriculture, Animal and Plant Health Inspection Service, Centers for Epidemiology and Animal Health, Fort Collins, Colorado, United States of America.
Ryan S MillerUnited States Department of Agriculture, Animal and Plant Health Inspection Service, Centers for Epidemiology and Animal Health, Fort Collins, Colorado, United States of America.
Jason E LombardUnited States Department of Agriculture, Animal and Plant Health Inspection Service, Centers for Epidemiology and Animal Health, Fort Collins, Colorado, United States of America.
Marleen WerkmanCenter for Complexity Science, Mathematics Institute, University of Warwick, Coventry, United Kingdom.
Matt J KeelingCenter for Complexity Science, Mathematics Institute, University of Warwick, Coventry, United Kingdom.
Uno WennergrenDepartment of Physics, Chemistry, and Biology, Linköping University, Linköping, Sweden.
Colleen T WebbDepartment of Biology, Colorado State University, Fort Collins, Colorado, United States of America.
Colorado State University · USUniversity of Warwick · GBLinköping University · SEUnited States Department of Agriculture · USAnimal and Plant Health Inspection Service · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Globalization has increased the potential for the introduction and spread of novel pathogens over large spatial scales necessitating continental-scale disease models to guide emergency preparedness. Livestock disease spread models, such as those for the 2001 foot-and-mouth disease (FMD) epidemic in the United Kingdom, represent some of the best case studies of large-scale disease spread. However, generalization of these models to explore disease outcomes in other systems, such as the United States's cattle industry, has been hampered by differences in system size and complexity and the absence of suitable livestock movement data. Here, a unique database of US cattle shipments allows estimation of synthetic movement networks that inform a near-continental scale disease model of a potential FMD-like (i.e., rapidly spreading) epidemic in US cattle. The largest epidemics may affect over one-third of the US and 120,000 cattle premises, but cattle movement restrictions from infected counties, as opposed to national movement moratoriums, are found to effectively contain outbreaks. Slow detection or weak compliance may necessitate more severe state-level bans for similar control. Such results highlight the role of large-scale disease models in emergency preparedness, particularly for systems lacking comprehensive movement and outbreak data, and the need to rapidly implement multi-scale contingency plans during a potential US outbreak.

Indexed as

MovementAnimalsCattleCattle DiseasesDisease OutbreaksGeographyModels, BiologicalPopulation DensityPrincipal Component AnalysisRisk FactorsUnited States

Identifiers

PMID24670977
PMCPMC3966763
OpenAlexW2147083255

What OpenQuestion holds

Textmetadata
LicenceCC0
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.