Multi-species temporal network of livestock movements for disease spread
Abstract Introduction The objective of this study is to show the importance of interspecies links and temporal network dynamics of a multi-species livestock movement network. Although both cattle and sheep networks have been previously studied, cattle-sheep multi-species networks have not generally...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2021-02-01
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| Series: | Applied Network Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s41109-021-00354-x |
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| author | Anne-Sophie Ruget Gianluigi Rossi P. Theo Pepler Gaël Beaunée Christopher J. Banks Jessica Enright Rowland R. Kao |
| author_facet | Anne-Sophie Ruget Gianluigi Rossi P. Theo Pepler Gaël Beaunée Christopher J. Banks Jessica Enright Rowland R. Kao |
| author_sort | Anne-Sophie Ruget |
| collection | DOAJ |
| description | Abstract Introduction The objective of this study is to show the importance of interspecies links and temporal network dynamics of a multi-species livestock movement network. Although both cattle and sheep networks have been previously studied, cattle-sheep multi-species networks have not generally been studied in-depth. The central question of this study is how the combination of cattle and sheep movements affects the potential for disease spread on the combined network. Materials and methods Our analysis considers static and temporal representations of networks based on recorded animal movements. We computed network-based node importance measures of two single-species networks, and compared the top-ranked premises with the ones in the multi-species network. We propose the use of a measure based on contact chains calculated in a network weighted with transmission probabilities to assess the importance of premises in an outbreak. To ground our investigation in infectious disease epidemiology, we compared this suggested measure with the results of disease simulation models with asymmetric probabilities of transmission between species. Results Our analysis of the temporal networks shows that the premises which are likely to drive the epidemic in this multi-species network differ from the ones in both the cattle and the sheep networks. Although sheep movements are highly seasonal, the estimated size of an epidemic is significantly larger in the multi-species network than in the cattle network, independently of the period of the year. Finally, we demonstrate that a measure based on contact chains allow us to identify around 30% of the key farms in a simulated epidemic, ignoring markets, whilst static network measures identify less than 10% of these farms. Conclusion Our results ascertain the importance of combining species networks, as well as considering layers of temporal livestock movements in detail for the study of disease spread. |
| first_indexed | 2024-12-13T11:53:57Z |
| format | Article |
| id | doaj.art-95321cb09cc54f9596d587fb575c308b |
| institution | Directory Open Access Journal |
| issn | 2364-8228 |
| language | English |
| last_indexed | 2024-12-13T11:53:57Z |
| publishDate | 2021-02-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Applied Network Science |
| spelling | doaj.art-95321cb09cc54f9596d587fb575c308b2022-12-21T23:47:16ZengSpringerOpenApplied Network Science2364-82282021-02-016112010.1007/s41109-021-00354-xMulti-species temporal network of livestock movements for disease spreadAnne-Sophie Ruget0Gianluigi Rossi1P. Theo Pepler2Gaël Beaunée3Christopher J. Banks4Jessica Enright5Rowland R. Kao6The Roslin Institute, University of EdinburghThe Roslin Institute, University of EdinburghInstitute of Biodiversity, Animal Health and Comparative Medicine, University of GlasgowThe Roslin Institute, University of EdinburghThe Roslin Institute, University of EdinburghSchool of Computing Science, University of GlasgowThe Roslin Institute, University of EdinburghAbstract Introduction The objective of this study is to show the importance of interspecies links and temporal network dynamics of a multi-species livestock movement network. Although both cattle and sheep networks have been previously studied, cattle-sheep multi-species networks have not generally been studied in-depth. The central question of this study is how the combination of cattle and sheep movements affects the potential for disease spread on the combined network. Materials and methods Our analysis considers static and temporal representations of networks based on recorded animal movements. We computed network-based node importance measures of two single-species networks, and compared the top-ranked premises with the ones in the multi-species network. We propose the use of a measure based on contact chains calculated in a network weighted with transmission probabilities to assess the importance of premises in an outbreak. To ground our investigation in infectious disease epidemiology, we compared this suggested measure with the results of disease simulation models with asymmetric probabilities of transmission between species. Results Our analysis of the temporal networks shows that the premises which are likely to drive the epidemic in this multi-species network differ from the ones in both the cattle and the sheep networks. Although sheep movements are highly seasonal, the estimated size of an epidemic is significantly larger in the multi-species network than in the cattle network, independently of the period of the year. Finally, we demonstrate that a measure based on contact chains allow us to identify around 30% of the key farms in a simulated epidemic, ignoring markets, whilst static network measures identify less than 10% of these farms. Conclusion Our results ascertain the importance of combining species networks, as well as considering layers of temporal livestock movements in detail for the study of disease spread.https://doi.org/10.1007/s41109-021-00354-xLivestock movementsMulti-speciesNetwork analysisTemporal networkStochastic simulations |
| spellingShingle | Anne-Sophie Ruget Gianluigi Rossi P. Theo Pepler Gaël Beaunée Christopher J. Banks Jessica Enright Rowland R. Kao Multi-species temporal network of livestock movements for disease spread Applied Network Science Livestock movements Multi-species Network analysis Temporal network Stochastic simulations |
| title | Multi-species temporal network of livestock movements for disease spread |
| title_full | Multi-species temporal network of livestock movements for disease spread |
| title_fullStr | Multi-species temporal network of livestock movements for disease spread |
| title_full_unstemmed | Multi-species temporal network of livestock movements for disease spread |
| title_short | Multi-species temporal network of livestock movements for disease spread |
| title_sort | multi species temporal network of livestock movements for disease spread |
| topic | Livestock movements Multi-species Network analysis Temporal network Stochastic simulations |
| url | https://doi.org/10.1007/s41109-021-00354-x |
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