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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 st...

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Autores principales: Hammami, Pachka, Widgren, Stefan, Grosbois, Vladimir, Apolloni, Andrea, Rose, Nicolas, Andraud, Mathieu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8989331/
https://www.ncbi.nlm.nih.gov/pubmed/35390068
http://dx.doi.org/10.1371/journal.pone.0266457
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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
collection PubMed
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.
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spelling pubmed-89893312022-04-08 Complex network analysis to understand trading partnership in French swine production Hammami, Pachka Widgren, Stefan Grosbois, Vladimir Apolloni, Andrea Rose, Nicolas Andraud, Mathieu PLoS One Research Article 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. Public Library of Science 2022-04-07 /pmc/articles/PMC8989331/ /pubmed/35390068 http://dx.doi.org/10.1371/journal.pone.0266457 Text en © 2022 Hammami et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hammami, Pachka
Widgren, Stefan
Grosbois, Vladimir
Apolloni, Andrea
Rose, Nicolas
Andraud, Mathieu
Complex network analysis to understand trading partnership in French swine production
title 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_short Complex network analysis to understand trading partnership in French swine production
title_sort complex network analysis to understand trading partnership in french swine production
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8989331/
https://www.ncbi.nlm.nih.gov/pubmed/35390068
http://dx.doi.org/10.1371/journal.pone.0266457
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