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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2022-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0266457 |
| _version_ | 1828729796004151296 |
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| author | Pachka Hammami Stefan Widgren Vladimir Grosbois Andrea Apolloni Nicolas Rose Mathieu Andraud |
| author_facet | Pachka Hammami Stefan Widgren Vladimir Grosbois Andrea Apolloni Nicolas Rose Mathieu Andraud |
| author_sort | Pachka Hammami |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-12T14:38:00Z |
| format | Article |
| id | doaj.art-440c5a75cd9d413ba9167bc6849ee5db |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-04-12T14:38:00Z |
| publishDate | 2022-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-440c5a75cd9d413ba9167bc6849ee5db2022-12-22T03:29:01ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-01174e026645710.1371/journal.pone.0266457Complex network analysis to understand trading partnership in French swine production.Pachka HammamiStefan WidgrenVladimir GrosboisAndrea ApolloniNicolas RoseMathieu AndraudThe 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.https://doi.org/10.1371/journal.pone.0266457 |
| spellingShingle | Pachka Hammami Stefan Widgren Vladimir Grosbois Andrea Apolloni Nicolas Rose Mathieu Andraud Complex network analysis to understand trading partnership in French swine production. PLoS ONE |
| 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 |
| url | https://doi.org/10.1371/journal.pone.0266457 |
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