Multi-species temporal network of livestock movements for disease spread

Ruget, A.-S., Rossi, G., Pepler, P. T. , Beaunée, G., Banks, C. J., Enright, J. and Kao, R. R. (2021) Multi-species temporal network of livestock movements for disease spread. Applied Network Science, 6, 15. (doi: 10.1007/s41109-021-00354-x)

[img] Text
234080.pdf - Published Version
Available under License Creative Commons Attribution.

3MB

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.

Item Type:Articles
Additional Information:This work was partially funded by the Scottish Government Rural and Environment Science and Analytical Services Division, as part of the Centre of Expertise on Animal Disease Outbreaks (EPIC). Funds have been provide by Roslin ISP2 (theme 3) - BBS/E/D/20002174 and BBSRC grant BB/P010598/1.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Rossi, Dr Gianluigi and Pepler, Dr Theo and Kao, Professor Rowland and Enright, Dr Jessica
Authors: Ruget, A.-S., Rossi, G., Pepler, P. T., Beaunée, G., Banks, C. J., Enright, J., and Kao, R. R.
College/School:College of Medical Veterinary and Life Sciences > Institute of Biodiversity Animal Health and Comparative Medicine
College of Science and Engineering > School of Computing Science
Journal Name:Applied Network Science
Publisher:SpringerOpen
ISSN:2364-8228
ISSN (Online):2364-8228
Published Online:18 February 2021
Copyright Holders:Copyright © 2021 The Authors
First Published:First published in Applied Network Science 6:15
Publisher Policy:Reproduced under a Creative Commons License

University Staff: Request a correction | Enlighten Editors: Update this record