Evidence map›Paper›PMID 26870738›Full record

ArticleFrontiers in veterinary science2016

Spatial and Functional Organization of Pig Trade in Different European Production Systems: Implications for Disease Prevention and Control.

Anne Relun, Vladimir Grosbois, José Manuel Sánchez-Vizcaíno, Tsviatko Alexandrov, Francesco Feliziani, Agnès Waret-Szkuta, Sophie Molia, Eric Marcel Charles Etter, Beatriz Martínez-López

Open access · goldAbstract read
In one paragraph

Article in Frontiers in veterinary science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
9.5field-weighted citation impact, top 2% 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

22 citing papers in PubMed, 48 citations in OpenAlex.

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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

9 authors at 6 institutions in 6 countries.

Anne RelunLe Centre de coopération internationale en recherche agronomique pour le développement (CIRAD), UPR Animal and Integrated Risk Management (AGIRs), Montpellier, France; Center for Animal Disease Modeling and Surveillance (CADMS), Department of Medicine & Epidemiology, School of Veterinary Medicine, University of California Davis, Davis, CA, USA.
Vladimir GrosboisLe Centre de coopération internationale en recherche agronomique pour le développement (CIRAD), UPR Animal and Integrated Risk Management (AGIRs) , Montpellier , France.
José Manuel Sánchez-VizcaínoAnimal Health Department, Complutense University of Madrid , Madrid , Spain.
Tsviatko AlexandrovBulgarian Food Safety Agency , Sofia , Bulgaria.
Francesco FelizianiIstituto Zooprofilattico Sperimentale dell'Umbria e delle Marche , Perugia , Italy.
Agnès Waret-SzkutaInstitut National Polytechnique-Ecole Nationale Vétérinaire de Toulouse (INP-ENVT) , Toulouse , France.
Sophie MoliaLe Centre de coopération internationale en recherche agronomique pour le développement (CIRAD), UPR Animal and Integrated Risk Management (AGIRs) , Montpellier , France.
Eric Marcel Charles EtterLe Centre de coopération internationale en recherche agronomique pour le développement (CIRAD), UPR Animal and Integrated Risk Management (AGIRs), Montpellier, France; Center for Animal Disease Modeling and Surveillance (CADMS), Department of Medicine & Epidemiology, School of Veterinary Medicine, University of California Davis, Davis, CA, USA.
Beatriz Martínez-LópezCenter for Animal Disease Modeling and Surveillance (CADMS), Department of Medicine & Epidemiology, School of Veterinary Medicine, University of California Davis , Davis, CA , USA.
Centre de Coopération Internationale en Recherche Agronomique pour le Développement · FRBulgarian Food Safety Agency · BGÉcole Nationale Vétérinaire de Toulouse · FRIstituto Zooprofilattico Sperimentale dell'Umbria e delle Marche · ITUniversidad Complutense de Madrid · ESUniversity of California, Davis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the complexity of live pig trade organization is a key factor to predict and control major infectious diseases, such as classical swine fever (CSF) or African swine fever (ASF). Whereas the organization of pig trade has been described in several European countries with indoor commercial production systems, little information is available on this organization in other systems, such as outdoor or small-scale systems. The objective of this study was to describe and compare the spatial and functional organization of live pig trade in different European countries and different production systems. Data on premise characteristics and pig movements between premises were collected during 2011 from Bulgaria, France, Italy, and Spain, which swine industry is representative of most of the production systems in Europe (i.e., commercial vs. small-scale and outdoor vs. indoor). Trade communities were identified in each country using the Walktrap algorithm. Several descriptive and network metrics were generated at country and community levels. Pig trade organization showed heterogeneous spatial and functional organization. Trade communities mostly composed of indoor commercial premises were identified in western France, northern Italy, northern Spain, and north-western Bulgaria. They covered large distances, overlapped in space, demonstrated both scale-free and small-world properties, with a role of trade operators and multipliers as key premises. Trade communities involving outdoor commercial premises were identified in western Spain, south-western and central France. They were more spatially clustered, demonstrated scale-free properties, with multipliers as key premises. Small-scale communities involved the majority of premises in Bulgaria and in central and Southern Italy. They were spatially clustered and had scale-free properties, with key premises usually being commercial production premises. These results indicate that a disease might spread very differently according to the production system and that key premises could be targeted to more cost-effectively control diseases. This study provides useful epidemiological information and parameters that could be used to design risk-based surveillance strategies or to more accurately model the risk of introduction or spread of devastating swine diseases, such as ASF, CSF, or foot-and-mouth disease.

Indexed as

communityinfectious diseasesmovementsnetwork analysisrisk-based surveillanceswine

Identifiers

PMID26870738
PMCPMC4740367
OpenAlexW2300014807

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.