Dissemin is shutting down on January 1st, 2025

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Inter Research, Diseases of Aquatic Organisms, 3(114), p. 177-187

DOI: 10.3354/dao02867

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Risk factors for outbreaks of infectious pancreatic necrosis (IPN) and associated mortality in Norwegian salmonid farming

Journal article published in 2015 by Britt Bang Jensen ORCID, Kristoffersen Ab
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Infectious pancreatic necrosis (IPN) has for many years been considered one of the most important restraints to the production of salmonids in European aquaculture. In Norway, the disease is responsible for high losses in post-smolts in the first few weeks after sea transfer. Despite the importance of IPN, there are few epidemiological studies on risk factors and mitigation strategies. In this paper, we present analyses of data from all cohorts put to sea in 2009 to 2012 on Norwegian marine salmonid farms. The data used were obtained from national registers on salmonid production and disease outbreaks. The results showed that the risk of IPN outbreak was higher for spring versus autumn cohorts, Atlantic salmon versus rainbow trout and for cohorts on farms with previous history of IPN. The risk increased with increasing cohort size and infection pressure, whereas increasing temperature and weight at sea transfer decreased the risk. Estimations from a model of cumulative mortality within the first 6 mo after sea transfer showed that mortality in cohorts with IPN increased to approximately 7.2% as compared to a 'baseline' cohort with a mortality of 3.4%. If the cohort had both IPN and pancreas disease (PD), the estimated mortality increased to 12.9%, and cohorts with both IPN, PD and heart and skeletal muscle inflammation (HSMI) had an estimated mortality of 16.6%, when all other significant factors were kept constant (these were cohort type, year, temperature at sea transfer and weight at sea transfer). Our results provide valuable inputs for mitigation strategies and for economic modelling of consequences of disease.