Peder A. Jansen

Sea lice as a density-dependent constraint to salmonid farming

Fisheries catches worldwide have shown no increase over the last two decades, while aquaculture has been booming. To cover the demand for fish in the growing human population, continued high growth rates in aquaculture are needed. A potential constraint to such growth is infectious diseases, as disease transmission rates are expected to increase with increasing densities of farmed fish. Using an extensive dataset from all farms growing salmonids along the Norwegian coast, we document that densities of farmed salmonids surrounding individual farms have a strong effect on farm levels of parasitic sea lice and efforts to control sea lice infections. Furthermore, increased intervention efforts have been unsuccessful in controlling elevated infection levels in high salmonid density areas in 2009–2010. Our results emphasize host density effects of farmed salmonids on the population dynamics of sea lice and suggest that parasitic sea lice represent a potent negative feedback mechanism that may limit sustainable spatial densities of farmed salmonids.

Risk factors for pancreas disease (PD) outbreaks in farmed Atlantic salmon and rainbow trout in Norway during 2003-2007.

Pancreas disease (PD) is an emerging infectious disease in farmed Atlantic salmon (Salmo salar L.) and rainbow trout (Oncorhynchus mykiss Walbaum) caused by salmonid alphavirus (SAV). The present study is a large scale study aiming at quantifying the probability of contracting PD in farmed salmonid cohorts in Norway due to exposure to risk factors that may be associated with specific transmission pathways for SAV, or may increase a cohorts susceptibility to PD. Monthly reports of numbers of fish and mean fish weight from all marine salmonid farm sites in Norway were used to identify cohorts of farmed salmonids. Only cohorts that were initiated and terminated during 2003-2007 were assembled for the study. Records of clinical diagnosis of PD on marine farm sites were used to identify PD case cohorts. In PD case cohorts, PD-outbreaks were defined to start the month the diagnosis was recorded and last until the cohort was terminated. All cohorts in which PD was not recorded were assigned to the control-class. In total 143 PD case cohorts and 1079 control cohorts were assembled. Risk factors were assigned to the cohorts and analysed using logistic regression by generalized additive models (GAM). We find that infection pressure, a variable designed to capture the potential for local disease spread, has a strong effect on the probability of recording a PD-outbreak in a cohort. The function describing the effect of infection pressure increased steeply as infection pressure increased from 0 to moderate values corresponding to having a mean sized neighbouring fish stock with PD at a distance of 2 km, after which the function levelled off. The study emphasises horizontal transmission pathways as important for the spread of PD in Norwegian salmon farming, and accordingly that bio-security measures aimed at controlling horizontal transmission are necessary in order to reduce the number of outbreaks of PD.

Integration of hydrodynamics into a statistical model on the spread of pancreas disease (PD) in salmon farming.

Pancreas disease (PD) is an emerging disease in salmon farming caused by the salmonid alphavirus (SAV). SAV is evidently spread horizontally between neighbouring salmon farms, but whether such transmission occurs by passive drift in the water current or via fomites is not known. We tested whether hydrodynamic modelling contributes to explain the spread of PD, in which case SAV is likely to spread by passive drift. We present a simple logistic regression model that accounts for the effect of PD in the neighbourhood on the probability of acquiring PD in cohorts of farmed salmonids from an area on the west coast of Norway between 2005 and 2008. For a given cohort, we calculated infection pressure (IP) based on Euclidean distance, seaway distance or estimated water contact to sites with PD, and compared the amount of variance explained in the regression model by the different variants of IP. Water contact between a discharging farm site and a receiving site was calculated by simulating particle discharge using a hydrodynamic model. IP estimated by water contact was the best predictor of PD cases and controls in the model, which performed significantly better than IP estimated by seaway distance or Euclidean distance. Since the spread of PD in the study area was best explained by modelled water velocity, we conclude that PD is likely to be spread by passive drift of SAV in the water current.

A stochastic model for the assessment of the transmission pathways of heart and skeleton muscle inflammation, pancreas disease and infectious salmon anaemia in marine fish farms in Norway.

Salmon farming is threatened, economically and ecologically, by infectious diseases. To reduce the risk of epidemics, authorities have developed regulations. These are based on quantitative understanding of pathways of infection, representing disease specific risks. A stochastic model was fitted to historical data, to estimate risk factors associated with competing spread mechanisms. Three infectious diseases were compared, heart and skeletal muscle inflammation (HSMI), pancreas disease (PD) and infectious salmon anaemia (ISA). This study was based on space-time data, from Norway from 2003 to 2007, describing the susceptible fish cohorts and the reported infections. Particular interest was given to seaway distances between farms and their local management organisation. The parameter measuring the effect of distance to an infectious fish farm was positive and significant for all diseases, implying that the risk involved with proximate infectious fish farms increased with decreasing distance. For HSMI and PD there was a significant effect of sharing a contact network with an infectious farm. For HSMI, but not for PD or ISA, there was a significant effect of previous infected cohorts on the same farm. The relative contribution of each transmission pathway was dominated by seaway distance for PD and HSMI, while other non-defined pathways dominated for ISA. This comparative study highlights that the three diseases have different patterns of spread, with important consequences for disease prevention and management.

Epidemiological Investigation of Infectious Salmon Anaemia (ISA) Outbreaks in Norway 2003-2005

Epidemiological information was summarized from 32 outbreaks of infectious salmon anaemia (ISA) on salmon farming sites in Norway in 2003-2005. Virus isolates from the outbreak sites were genotyped, and the genotyping was used to assess possible associations between outbreak sites due to adjacent location, sharing fish farming authorisation, sharing smolt suppliers or sharing broodfish origin of the fish. The ISA outbreaks were distributed along most of the Norwegian coast and showed a variable clinical picture. The virus genotypes clustered into three genogroups. Pairs of outbreak sites matched for adjacent location or registered under the same authorisation, all shared genogroup, which was a significantly higher number of corresponding genogroups than expected by chance. For outbreak sites sharing smolt suppliers, corresponding genogroups appeared in 7 out of 12 matched pairs, which was not significant. An evaluation of broodfish origin associated with genogroups did not support transmission linked to broodfish origin. In conclusion, genotyping of virus isolates from ISA outbreaks supports associations between adjacent outbreaks. This is consistent with horizontal transmission. The present study failed to find evidence for vertical transmission (patterns of genogroups related to smolt suppliers or broodfish companies were not identified).

A stochastic model for infectious salmon anemia (ISA) in Atlantic salmon farming

Infectious salmon anemia (ISA) is one of the main infectious diseases in Atlantic salmon farming with major economical implications. Despite the strong regulatory interventions, the ISA epidemic is not under control, worldwide. We study the data covering salmon farming in Norway from 2002 to 2005 and propose a stochastic space-time model for the transmission of the virus. We model seaway transmission between farm sites, transmission through shared management and infrastructure, biomass effects and other potential pathways within the farming industry. We find that biomass has an effect on infectiousness, the local contact network and seaway distance of 5 km represent similar risks, but a large component of risk originates from other sources, among which are possibly infected salmon smolt and boat traffic.

Modelling the spread of infectious salmon anaemia among salmon farms based on seaway distances between farms and genetic relationships between infectious salmon anaemia virus isolates

Infectious salmon anaemia (ISA) is an important infectious disease in Atlantic salmon farming causing recurrent epidemic outbreaks worldwide. The focus of this paper is on tracing the spread of ISA among Norwegian salmon farms. To trace transmission pathways for the ISA virus (ISAV), we use phylogenetic relationships between virus isolates in combination with space–time data on disease occurrences. The rate of ISA infection of salmon farms is modelled stochastically, where seaway distances between farms and genetic distances between ISAV isolates from infected farms play prominent roles. The model was fitted to data covering all cohorts of farmed salmon and the history of all farms with ISA between 2003 and summer 2009. Both seaway and genetic distances were significantly associated with the rate of ISA infection. The fitted model predicts that the risk of infection from a neighbourhood infectious farm decreases with increasing seaway distance between the two farms. Furthermore, for a given infected farm with a given ISAV genotype, the source of infection is significantly more likely to be ISAV of a small genetic distance than of moderate or large genetic distances. Nearly half of the farms with ISA in the investigated period are predicted to have been infected by an infectious farm in their neighbourhood, whereas the remaining half of the infected farms had unknown sources. For many of the neighbourhood infected farms, it was possible to point out one or a few infectious farms as the most probable sources of infection. This makes it possible to map probable infection pathways.

Use of molecular epidemiology to trace transmission pathways for infectious salmon anaemia virus (ISAV) in Norwegian salmon farming.

BACKGROUND Infectious Salmon Anaemia (ISA) is a disease affecting farmed Atlantic salmon, and most salmon producing countries have experienced ISA outbreaks. The aim of the present study was to use epidemiological and viral sequence information to trace transmission pathways for ISA virus (ISAV) in Norwegian salmon farming. METHODS The study covers a period from January 2007 to July 2009 with a relatively high rate of ISA outbreaks, including a large cluster of outbreaks that emerged in Northern Norway (the North-cluster). Farms with ISA outbreaks and neighbouring salmon farms (At-risk-sites) were tested for the presence of ISAV, and epidemiological information was collected. ISAV hemagglutinin-esterase (HE) and fusion (F) protein genes were sequenced and phylogenetic analyses were performed. Associations between sequence similarities and salmon population data were analysed to substantiate possible transmission pathways. RESULTS There was a high degree of genetic similarity between ISAV isolates within the North-cluster. ISAV was detected in 12 of 28 At-risk-sites, and a high proportion of the viruses were identified as putative low virulent genotypes harbouring the full length highly polymorphic region (HPR); HPR0 of the HE protein and the amino acid glutamine (Q) in the F protein at position 266. The sequences from HPR0/F (Q(266)) genotypes revealed larger genetic variation, lower viral loads and lower prevalence of infection than HPR-deleted genotypes. Seaway distance between salmon farms was the only robust explanatory variable to explain genetic similarity between ISAV isolates. DISCUSSION We suggest that a single HPR-deleted genotype of ISAV has spread between salmon farms in the North-cluster. Furthermore, we find that HPR0/F (Q(266)) genotypes are frequently present in farmed populations of Atlantic salmon. From this, we anticipate a population dynamics of ISAV portrayed by low virulent genotypes occasionally transitioning into virulent genotypes, causing solitary outbreaks or local epidemics through local transmission.

Space-time modelling of the spread of salmon lice between and within Norwegian marine salmon farms.

Parasitic salmon lice are potentially harmful to salmonid hosts and farm produced lice pose a threat to wild salmonids. To control salmon lice infections in Norwegian salmonid farming, numbers of lice are regularly counted and lice abundance is reported from all salmonid farms every month. We have developed a stochastic space-time model where monthly lice abundance is modelled simultaneously for all farms. The set of farms is regarded as a network where the degree of contact between farms depends on their seaway distance. The expected lice abundance at each farm is modelled as a function of i) lice abundance in previous months at the same farm, ii) at neighbourhood farms, and iii) other, unspecified sources. In addition, the model includes explanatory variables such as seawater temperature and farm-numbers of fish. The model gives insight into factors that affect salmon lice abundance and contributing sources of infection. New findings in this study were that 66% of the expected salmon lice abundance was attributed to infection within farms, 28% was attributed to infection from neighbourhood farms and 6% to non-specified sources of infection. Furthermore, we present the relative risk of infection between neighbourhood farms as a function of seaway distance, which can be viewed as a between farm transmission kernel for salmon lice. The present modelling framework lays the foundation for development of future scenario simulation tools for examining the spread and abundance of salmon lice on farmed salmonids under different control regimes.

Large scale modelling of salmon lice (Lepeophtheirus salmonis) infection pressure based on lice monitoring data from Norwegian salmonid farms

Infection by parasitic sea lice is a substantial problem in industrial scale salmon farming. To control the problem, Norwegian salmonid farms are not permitted to exceed a threshold level of infection on their fish, and farms are required to monitor and report lice levels on a weekly basis to ensure compliance with the regulation. In the present study, we combine the monitoring data with a deterministic model for salmon lice population dynamics to estimate farm production of infectious lice stages. Furthermore, we use an empirical estimate of the relative risk of salmon lice transmission between farms, that depend on inter-farm distances, to estimate the external infection pressure at a farm site, i.e. the infection pressure from infective salmon lice of neighbouring farm origin. Finally, we test whether our estimates of infection pressure from neighbouring farms as well as internal within farm infection pressure, predicts subsequent development of infection in cohorts of farmed salmonids in their initial phase of marine production. We find that estimated external infection pressure is a main predictor of salmon lice population dynamics in newly stocked cohorts of salmonids. Our results emphasize the importance of keeping the production of infectious lice stages at low levels within local networks of salmon farms. Our model can easily be implemented for real time estimation of infection pressure at the national scale, utilizing the masses of data generated through the compulsory lice monitoring in salmon farms. The implementation of such a system should give the salmon industry greater predictability with respect to salmon lice infection levels, and aid the decision making process when the development of new farm sites are planned.