Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/29702
Appears in Collections:Aquaculture Journal Articles
Peer Review Status: Refereed
Title: The Contact Structure of Great Britain's Salmon and Trout Aquaculture Industry
Author(s): Jones, Anne E
Munro, Lorna A
Green, Darren M
Morgan, Kenton L
Murray, Alexander G
Norman, Rachel
Salama, Nabeil K G
Ryder, David
Taylor, Nick G H
Thrush, Mark A
Wallace, I Stuart
Sharkey, Kieran J
Keywords: Aquaculture
network
graph
giant component
fish diseases
control policy
Issue Date: Sep-2019
Date Deposited: 20-Jun-2019
Citation: Jones AE, Munro LA, Green DM, Morgan KL, Murray AG, Norman R, Salama NKG, Ryder D, Taylor NGH, Thrush MA, Wallace IS & Sharkey KJ (2019) The Contact Structure of Great Britain's Salmon and Trout Aquaculture Industry. Epidemics, 28, Art. No.: 100342. https://doi.org/10.1016/j.epidem.2019.05.001
Abstract: We analyse the network structure of the British salmonid aquaculture industry from the perspective of infectious disease control. We combine for the first time live fish transport (or movement) data covering England and Wales with data covering Scotland and include network layers representing potential transmission by rivers, sea water and local transmission via human or animal vectors in the immediate vicinity of each farm or fishery site. We find that 7.2% of all live fish transports cross the England-Scotland border and network analysis shows that 87% of English and Welsh sites and 72% of Scottish sites are reachable from cross-border connections via live fish transports alone. Consequently, from a disease-control perspective, the contact structures of England and Wales and of Scotland should not be considered in isolation. We also show that large epidemics require the live fish movement network and so control strategies targeting movements can be very effective. While there is relatively low risk of widespread epidemics on the live fish transport network alone, the potential risk is substantially amplified by the combined interaction of multiple network layers.
DOI Link: 10.1016/j.epidem.2019.05.001
Rights: This is an open access article distributed under the terms of the Creative Commons CC-BY license (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. You are not required to obtain permission to reuse this article.
Licence URL(s): http://creativecommons.org/licenses/by/4.0/

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