Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/18195
Appears in Collections:Aquaculture Journal Articles
Peer Review Status: Refereed
Title: Seasonality in live fish movements and its effects on epidemic dynamics
Authors: Werkman, Marleen
Murray, Alexander G
Munro, Lorna Ann
Turnbull, James
Green, Darren
Contact Email: j.f.turnbull@stir.ac.uk
Keywords: Networks
Disease transmission
Graph
Control strategies
Simulation model
Issue Date: Jan-2014
Publisher: Elsevier
Citation: Werkman M, Murray AG, Munro LA, Turnbull J & Green D (2014) Seasonality in live fish movements and its effects on epidemic dynamics, Aquaculture, 418-419, pp. 72-78.
Abstract: Live fish movements between salmon farms risk spreading pathogens, and movements between freshwater farms (FW-FW) or from freshwater to seawater (FW-SW) show clear seasonality. In this study, we quantify the effects of seasonality of live fish movements on epidemic dynamics, using a network model populated with data from live fish movements between Scottish salmon farms from 2002 to 2004. We used three types of networks: A) timing and pair-wise movements between farms were as observed; B) as network A, but with a random reordering of FW-FW and FW-SW movements; and C) number of movements were kept the same as in the data, but connection between nodes was random. We compared the time-course of simulated epidemics in a stochastic model for all three networks. We showed that seasonality had the strongest effect in networks B and C, especially when local transmission was high, and this effect was stronger in SW farms compared with FW farms.
Type: Journal Article
URI: http://hdl.handle.net/1893/18195
DOI Link: http://dx.doi.org/10.1016/j.aquaculture.2013.10.001
Rights: The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.
Affiliation: University of Stirling
Scottish Government - Enterprise, Environment & Digital - Marine Scotland
Scottish Government - Enterprise, Environment & Digital - Marine Scotland
Aquaculture
Aquaculture

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