Abstract

Doc number: 172

Abstract

Background: Outbreaks of pancreas disease (PD) greatly contribute to economic losses due to high mortality, control measures, interrupted production cycles, reduced feed conversion and flesh quality in the aquaculture industries in European salmon-producing countries. The overall objective of this study was to evaluate an effect of potential factors contributing to PD occurrence accounting for spatial congruity of neighboring infected sites, and then create quantitative risk maps for predicting PD occurrence. The study population included active Atlantic salmon farming sites located in the coastal area of 6 southern counties of Norway (where most of PD outbreaks have been reported so far) from 1 January 2009 to 31 December 2010.

Results: Using a Bayesian modeling approach, with and without spatial component, the final model included site latitude, site density, PD history, and local biomass density. Clearly, the PD infected sites were spatially clustered; however, the cluster was well explained by the covariates of the final model. Based on the final model, we produced a map presenting the predicted probability of the PD occurrence in the southern part of Norway. Subsequently, the predictive capacity of the final model was validated by comparing the predicted probabilities with the observed PD outbreaks in 2011.

Conclusions: The framework of the study could be applied for spatial studies of other infectious aquatic animal diseases.

Details

Title
Risk map and spatial determinants of pancreas disease in the marine phase of Norwegian Atlantic salmon farming sites
Author
Tavornpanich, Saraya; Paul, Mathilde; Viljugrein, Hildegunn; Abrial, David; Jimenez, Daniel; Brun, Edgar
Pages
172
Publication year
2012
Publication date
2012
Publisher
BioMed Central
e-ISSN
17466148
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1221532722
Copyright
© 2012 Tavornpanich et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.