Risk map and spatial determinants of pancreas disease in the marine phase of Norwegian Atlantic salmon farming sites
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 o...
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ftbiomed:oai:biomedcentral.com:1746-6148-8-172 2023-05-15T15:31:32+02:00 Risk map and spatial determinants of pancreas disease in the marine phase of Norwegian Atlantic salmon farming sites Tavornpanich, Saraya Paul, Mathilde Viljugrein, Hildegunn Abrial, David Jimenez, Daniel Brun, Edgar 2012-09-24 http://www.biomedcentral.com/1746-6148/8/172 en eng BioMed Central Ltd. http://www.biomedcentral.com/1746-6148/8/172 Copyright 2012 Tavornpanich et al.; licensee BioMed Central Ltd. Pancreas disease Aquatic epidemiology Spatial analysis Disease mapping Bayesian modeling Research article 2012 ftbiomed 2012-12-09T00:58:36Z 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. Article in Journal/Newspaper Atlantic salmon BioMed Central Norway |
institution |
Open Polar |
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BioMed Central |
op_collection_id |
ftbiomed |
language |
English |
topic |
Pancreas disease Aquatic epidemiology Spatial analysis Disease mapping Bayesian modeling |
spellingShingle |
Pancreas disease Aquatic epidemiology Spatial analysis Disease mapping Bayesian modeling Tavornpanich, Saraya Paul, Mathilde Viljugrein, Hildegunn Abrial, David Jimenez, Daniel Brun, Edgar Risk map and spatial determinants of pancreas disease in the marine phase of Norwegian Atlantic salmon farming sites |
topic_facet |
Pancreas disease Aquatic epidemiology Spatial analysis Disease mapping Bayesian modeling |
description |
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. |
format |
Article in Journal/Newspaper |
author |
Tavornpanich, Saraya Paul, Mathilde Viljugrein, Hildegunn Abrial, David Jimenez, Daniel Brun, Edgar |
author_facet |
Tavornpanich, Saraya Paul, Mathilde Viljugrein, Hildegunn Abrial, David Jimenez, Daniel Brun, Edgar |
author_sort |
Tavornpanich, Saraya |
title |
Risk map and spatial determinants of pancreas disease in the marine phase of Norwegian Atlantic salmon farming sites |
title_short |
Risk map and spatial determinants of pancreas disease in the marine phase of Norwegian Atlantic salmon farming sites |
title_full |
Risk map and spatial determinants of pancreas disease in the marine phase of Norwegian Atlantic salmon farming sites |
title_fullStr |
Risk map and spatial determinants of pancreas disease in the marine phase of Norwegian Atlantic salmon farming sites |
title_full_unstemmed |
Risk map and spatial determinants of pancreas disease in the marine phase of Norwegian Atlantic salmon farming sites |
title_sort |
risk map and spatial determinants of pancreas disease in the marine phase of norwegian atlantic salmon farming sites |
publisher |
BioMed Central Ltd. |
publishDate |
2012 |
url |
http://www.biomedcentral.com/1746-6148/8/172 |
geographic |
Norway |
geographic_facet |
Norway |
genre |
Atlantic salmon |
genre_facet |
Atlantic salmon |
op_relation |
http://www.biomedcentral.com/1746-6148/8/172 |
op_rights |
Copyright 2012 Tavornpanich et al.; licensee BioMed Central Ltd. |
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1766362063127445504 |