Complex network analysis to understand trading partnership in French swine production

The circulation of livestock pathogens in the pig industry is strongly related to animal movements. Epidemiological models developed to understand the circulation of pathogens within the industry should include the probability of transmission via between-farm contacts. The pig industry presents a structured network in time and space, whose composition changes over time. Therefore, to improve the predictive capabilities of epidemiological models, it is important to identify the drivers of farmers' choices in terms of trade partnerships. Combining complex network analysis approaches and exponential random graph models, this study aims to analyze patterns of the swine industry network and identify key factors responsible for between-farm contacts at the French scale. The analysis confirms the topological stability of the network over time while highlighting the important roles of companies, types of farm, farm sizes, outdoor housing systems and batch-rearing systems. Both approaches revealed to be complementary and very effective to understand the drivers of the network. Results of this study are promising for future developments of epidemiological models for livestock diseases. This study is part of the One Health European Joint Programme: BIOPIGEE.

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Main Authors: Hammami, Pachka, Widgren, Stefan, Grosbois, Vladimir, Apolloni, Andrea, Rose, Nicolas, Andraud, Mathieu
Format: article biblioteca
Language:eng
Subjects:L73 - Maladies des animaux, L01 - Élevage - Considérations générales, U10 - Informatique, mathématiques et statistiques, analyse de système, épidémiologie, transmission des maladies, porcin, maladie des animaux, modélisation, http://aims.fao.org/aos/agrovoc/c_7581, http://aims.fao.org/aos/agrovoc/c_2615, http://aims.fao.org/aos/agrovoc/c_2329, http://aims.fao.org/aos/agrovoc/c_7555, http://aims.fao.org/aos/agrovoc/c_426, http://aims.fao.org/aos/agrovoc/c_230ab86c,
Online Access:http://agritrop.cirad.fr/604002/
http://agritrop.cirad.fr/604002/1/604002.pdf
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spelling dig-cirad-fr-6040022024-04-25T08:33:45Z http://agritrop.cirad.fr/604002/ http://agritrop.cirad.fr/604002/ Complex network analysis to understand trading partnership in French swine production. Hammami Pachka, Widgren Stefan, Grosbois Vladimir, Apolloni Andrea, Rose Nicolas, Andraud Mathieu. 2022. PloS One, 17 (4):e0266457, 27 p.https://doi.org/10.1371/journal.pone.0266457 <https://doi.org/10.1371/journal.pone.0266457> Complex network analysis to understand trading partnership in French swine production Hammami, Pachka Widgren, Stefan Grosbois, Vladimir Apolloni, Andrea Rose, Nicolas Andraud, Mathieu eng 2022 PloS One L73 - Maladies des animaux L01 - Élevage - Considérations générales U10 - Informatique, mathématiques et statistiques analyse de système épidémiologie transmission des maladies porcin maladie des animaux modélisation http://aims.fao.org/aos/agrovoc/c_7581 http://aims.fao.org/aos/agrovoc/c_2615 http://aims.fao.org/aos/agrovoc/c_2329 http://aims.fao.org/aos/agrovoc/c_7555 http://aims.fao.org/aos/agrovoc/c_426 http://aims.fao.org/aos/agrovoc/c_230ab86c The circulation of livestock pathogens in the pig industry is strongly related to animal movements. Epidemiological models developed to understand the circulation of pathogens within the industry should include the probability of transmission via between-farm contacts. The pig industry presents a structured network in time and space, whose composition changes over time. Therefore, to improve the predictive capabilities of epidemiological models, it is important to identify the drivers of farmers' choices in terms of trade partnerships. Combining complex network analysis approaches and exponential random graph models, this study aims to analyze patterns of the swine industry network and identify key factors responsible for between-farm contacts at the French scale. The analysis confirms the topological stability of the network over time while highlighting the important roles of companies, types of farm, farm sizes, outdoor housing systems and batch-rearing systems. Both approaches revealed to be complementary and very effective to understand the drivers of the network. Results of this study are promising for future developments of epidemiological models for livestock diseases. This study is part of the One Health European Joint Programme: BIOPIGEE. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/604002/1/604002.pdf text cc_by info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ https://doi.org/10.1371/journal.pone.0266457 10.1371/journal.pone.0266457 info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0266457 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1371/journal.pone.0266457 info:eu-repo/semantics/reference/purl/https://github.com/Pachka/SwineNet info:eu-repo/grantAgreement/EC/H2020/773830//(EU) Promoting One Health in Europe through joint actions on foodborne zoonoses, antimicrobial resistance and emerging microbiological hazards/One Health EJP
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic L73 - Maladies des animaux
L01 - Élevage - Considérations générales
U10 - Informatique, mathématiques et statistiques
analyse de système
épidémiologie
transmission des maladies
porcin
maladie des animaux
modélisation
http://aims.fao.org/aos/agrovoc/c_7581
http://aims.fao.org/aos/agrovoc/c_2615
http://aims.fao.org/aos/agrovoc/c_2329
http://aims.fao.org/aos/agrovoc/c_7555
http://aims.fao.org/aos/agrovoc/c_426
http://aims.fao.org/aos/agrovoc/c_230ab86c
L73 - Maladies des animaux
L01 - Élevage - Considérations générales
U10 - Informatique, mathématiques et statistiques
analyse de système
épidémiologie
transmission des maladies
porcin
maladie des animaux
modélisation
http://aims.fao.org/aos/agrovoc/c_7581
http://aims.fao.org/aos/agrovoc/c_2615
http://aims.fao.org/aos/agrovoc/c_2329
http://aims.fao.org/aos/agrovoc/c_7555
http://aims.fao.org/aos/agrovoc/c_426
http://aims.fao.org/aos/agrovoc/c_230ab86c
spellingShingle L73 - Maladies des animaux
L01 - Élevage - Considérations générales
U10 - Informatique, mathématiques et statistiques
analyse de système
épidémiologie
transmission des maladies
porcin
maladie des animaux
modélisation
http://aims.fao.org/aos/agrovoc/c_7581
http://aims.fao.org/aos/agrovoc/c_2615
http://aims.fao.org/aos/agrovoc/c_2329
http://aims.fao.org/aos/agrovoc/c_7555
http://aims.fao.org/aos/agrovoc/c_426
http://aims.fao.org/aos/agrovoc/c_230ab86c
L73 - Maladies des animaux
L01 - Élevage - Considérations générales
U10 - Informatique, mathématiques et statistiques
analyse de système
épidémiologie
transmission des maladies
porcin
maladie des animaux
modélisation
http://aims.fao.org/aos/agrovoc/c_7581
http://aims.fao.org/aos/agrovoc/c_2615
http://aims.fao.org/aos/agrovoc/c_2329
http://aims.fao.org/aos/agrovoc/c_7555
http://aims.fao.org/aos/agrovoc/c_426
http://aims.fao.org/aos/agrovoc/c_230ab86c
Hammami, Pachka
Widgren, Stefan
Grosbois, Vladimir
Apolloni, Andrea
Rose, Nicolas
Andraud, Mathieu
Complex network analysis to understand trading partnership in French swine production
description The circulation of livestock pathogens in the pig industry is strongly related to animal movements. Epidemiological models developed to understand the circulation of pathogens within the industry should include the probability of transmission via between-farm contacts. The pig industry presents a structured network in time and space, whose composition changes over time. Therefore, to improve the predictive capabilities of epidemiological models, it is important to identify the drivers of farmers' choices in terms of trade partnerships. Combining complex network analysis approaches and exponential random graph models, this study aims to analyze patterns of the swine industry network and identify key factors responsible for between-farm contacts at the French scale. The analysis confirms the topological stability of the network over time while highlighting the important roles of companies, types of farm, farm sizes, outdoor housing systems and batch-rearing systems. Both approaches revealed to be complementary and very effective to understand the drivers of the network. Results of this study are promising for future developments of epidemiological models for livestock diseases. This study is part of the One Health European Joint Programme: BIOPIGEE.
format article
topic_facet L73 - Maladies des animaux
L01 - Élevage - Considérations générales
U10 - Informatique, mathématiques et statistiques
analyse de système
épidémiologie
transmission des maladies
porcin
maladie des animaux
modélisation
http://aims.fao.org/aos/agrovoc/c_7581
http://aims.fao.org/aos/agrovoc/c_2615
http://aims.fao.org/aos/agrovoc/c_2329
http://aims.fao.org/aos/agrovoc/c_7555
http://aims.fao.org/aos/agrovoc/c_426
http://aims.fao.org/aos/agrovoc/c_230ab86c
author Hammami, Pachka
Widgren, Stefan
Grosbois, Vladimir
Apolloni, Andrea
Rose, Nicolas
Andraud, Mathieu
author_facet Hammami, Pachka
Widgren, Stefan
Grosbois, Vladimir
Apolloni, Andrea
Rose, Nicolas
Andraud, Mathieu
author_sort Hammami, Pachka
title Complex network analysis to understand trading partnership in French swine production
title_short Complex network analysis to understand trading partnership in French swine production
title_full Complex network analysis to understand trading partnership in French swine production
title_fullStr Complex network analysis to understand trading partnership in French swine production
title_full_unstemmed Complex network analysis to understand trading partnership in French swine production
title_sort complex network analysis to understand trading partnership in french swine production
url http://agritrop.cirad.fr/604002/
http://agritrop.cirad.fr/604002/1/604002.pdf
work_keys_str_mv AT hammamipachka complexnetworkanalysistounderstandtradingpartnershipinfrenchswineproduction
AT widgrenstefan complexnetworkanalysistounderstandtradingpartnershipinfrenchswineproduction
AT grosboisvladimir complexnetworkanalysistounderstandtradingpartnershipinfrenchswineproduction
AT apolloniandrea complexnetworkanalysistounderstandtradingpartnershipinfrenchswineproduction
AT rosenicolas complexnetworkanalysistounderstandtradingpartnershipinfrenchswineproduction
AT andraudmathieu complexnetworkanalysistounderstandtradingpartnershipinfrenchswineproduction
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