Bacterial Skin Microbiota of Seabass from Aegean Fish Farms and Antibiotic Susceptibility of Psychrotrophic Pseudomonas.

Farming seabass (Dicentrarchus labrax) is an essential activity in the Mediterranean basin including the Aegean Sea. The main seabass producer is Turkey accounting for 155,151 tons of production in 2021. In this study, skin swabs of seabass farmed in the Aegean Sea were analysed with regard to the isolation and identification of Pseudomonas. Bacterial microbiota of skin samples (n = 96) from 12 fish farms were investigated using next-generation sequencing (NGS) and metabarcoding analysis. The results demonstrated that Proteobacteria was the dominant bacterial phylum in all samples. At the species level, Pseudomonas lundensis was identified in all samples. Pseudomonas, Shewanella, and Flavobacterium were identified using conventional methods and a total of 46 viable (48% of all NGS+) Pseudomonas were isolated in seabass swab samples. Additionally, antibiotic susceptibility was determined according to standards of the European Committee on Antimicrobial Susceptibility Testing (EUCAST) and Clinical and Laboratory Standards Institute (CLSI) in psychrotrophic Pseudomonas. Pseudomonas strains were tested for susceptibility to 11 antibiotics (piperacillin-tazobactam, gentamicin, tobramycin, amikacin, doripenem, meropenem, imipenem, levofloxacin, ciprofloxacin, norfloxacin, and tetracycline) from five different groups of antibiotics (penicillins, aminoglycosides, carbapenems, fluoroquinolones, and tetracyclines). The antibiotics chosen were not specifically linked to usage by the aquaculture industry. According to the EUCAST and CLSI, three and two Pseudomonas strains were found to be resistant to doripenem and imipenem (E-test), respectively. All strains were susceptible to piperacillin-tazobactam, amikacin, levofloxacin, and tetracycline. Our data provide insight into different bacteria that are prevalent in the skin microbiota of seabass sampled from the Aegean Sea in Turkey, and into the antibiotic resistance of psychrotrophic Pseudomonas spp.

Stability and Activity of Interferon Beta to Treat Idiopathic Pulmonary Fibrosis with Different Nebulizer Technologies.

Background: Idiopathic pulmonary fibrosis (IPF) is a serious lung disease characterized by lung scarring, which results in breathing difficulty. Currently, patients with IPF exhibit a poor survival rate and have access to very limited therapeutic options. Interferon beta (IFN-ß) has been approved by the U.S. Food and Drug Administration (FDA) for the treatment of relapsing forms of multiple sclerosis, and it has also been shown to exhibit therapeutic potential in IPF. However, clinical use of IFN-ß did not lead to improved overall survival in IPF patients in existing studies. One possibility is the limited efficiency of IFN-ß delivery through intravenous or subcutaneous injection. Materials and Methods: The aerosol particle size distribution was determined with a laser diffraction particle size analyzer to characterize the droplet size and fine particle fraction generated by three types of nebulizers: jet, ultrasonic, and mesh. A breathing simulator was used to assess the delivery efficiency of IFN-ß, and the temperature in the medication reservoirs was monitored with a thermocouple during nebulization. To further evaluate the antifibrotic activity of IFN-ß pre- and postnebulization, bleomycin (BLM)- or transforming growth factor-beta (TGF-ß)-treated human lung fibroblast (HLF) cells were used. Cell viability was measured by 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay. Transwell migration assay and Q-PCR analysis were used to evaluate cell migration and the myofibroblast differentiation ability, respectively. IFN-ß protein samples were prepared using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) sample loading buffer, and the expression of IFN-ß was assessed by western blotting. Results: Among the current drug delivery systems, aerosolized medication has shown increased efficacy of drug delivery for treating respiratory diseases when compared with parenteral drugs. It was found that neither the structural integrity nor the biological function of nebulized IFN-ß was compromised by the nebulization process of the mesh nebulizer. In addition, in BLM dose-response or TGF-ß-induced lung fibroblast proliferation assays, these effects could be reversed by both parenteral and inhaled IFN-ß nebulized with the mesh nebulizer. Nebulized IFN-ß with the mesh nebulizer also significantly inhibited the migration and myofibroblast differentiation ability of TGF-ß-treated HLF cells. Conclusions: The investigations revealed the potential efficacy of IFN-ß in the treatment of IPF with the mesh nebulizer, demonstrating the higher efficiency of IFN-ß delivered through the mesh nebulizer.

Solving Patient Allocation Problem during an Epidemic Dengue Fever Outbreak by Mathematical Modelling.

Dengue fever is a mosquito-borne disease that has rapidly spread throughout the last few decades. Most preventive mechanisms to deal with the disease focus on the eradication of the vector mosquito and vaccination campaigns. However, appropriate mechanisms of response are indispensable to face the consequent events when an outbreak takes place. This study applied single and multiple objective linear programming models to optimize the allocation of patients and additional resources during an epidemic dengue fever outbreak, minimizing the summation of the distance travelled by all patients. An empirical study was set in Ciudad del Este, Paraguay. Data provided by a privately run health insurance cooperative was used to verify the applicability of the models in this study. The results can be used by analysts and decision makers to solve patient allocation problems for providing essential medical care during an epidemic dengue fever outbreak.

Mapping the knowledge of the main diseases affecting sea bass and sea bream in Mediterranean.

Good knowledge on the disease situation and its impact on production is a base mechanism for designing health surveillance, risk analysis and biosecurity systems. Mediterranean marine fish farming, as any aquaculture production, is affected by various infectious diseases. However, seabass and seabream, the main produced species, are not listed as susceptible host species for the notifiable pathogens listed in the current EU legislation, which generates a lack of systematic reporting. The results presented in this study come from a survey directly to fish farms (50 hatchery and on-growing units from 10 Mediterranean countries), with data from 2015 to 2017, conducted by the H2020 project MedAID. Seabass showed a higher survival rate (85%) through a production cycle than seabream (80%) in spite of equal mortality due to pathogen infections (10%). The differences in survival may be explained by mortality 'of other causes'. Seabream and seabass have different disease profiles, and the profile is slightly different between geographical regions. Among the most important diseases, tenacibaculosis and vibriosis were identified in seabass and Sparicotyle chrysophrii (a gill fluke) and nodavirus in seabream. Correlating mortality data to management variables showed that increasing density, buying fingerlings from external sources and treatments due to disease are factors that negatively influence mortality rate. Most of the surveyed farms did not keep sufficient quality data to implement good health status reports and perform detailed impact studies, which shows the necessity of updating the current legislative framework to provide the basis for better reporting of relevant pathogens in the Mediterranean basin.

Field Evaluation of Diagnostic Test Sensitivity and Specificity for Salmonid Alphavirus (SAV) Infection and Pancreas Disease (PD) in Farmed Atlantic salmon (Salmo salar L.) in Norway Using Bayesian Latent Class Analysis.

Salmonid alphavirus (SAV) is the OIE-listed, viral cause of pancreas disease (PD) in farmed Atlantic salmon. SAV is routinely detected by PCR-methods while typical histopathological lesions are additionally used to confirm the diagnosis. Field evaluation of diagnostic test performance is essential to ensure confidence in a test's ability to predict the infection or disease status of a target animal. For most tests used in aquaculture, characteristics like sensitivity (Se) and specificity (Sp) at the analytical level may be known. Few tests are, however, evaluated at the diagnostic level according to the OIE standard. In the present work, we estimated diagnostic test sensitivity (DSe) and diagnostic test specificity (DSp) for five laboratory tests used for SAV detection. As there is no gold standard, the study was designed using Bayesian latent class analysis. Real-time RT-PCR, cell culture, histopathology, virus neutralization test, and immunohistochemistry were compared using samples taken from three different farmed Atlantic salmon populations with different infection status; one population regarded negative, one in an early stage of infection, and one in a later stage of infection. The average fish weight in the three populations was 2.0, 1.6, and 1.5 kg, respectively. The DSe and DSp of real-time RT-PCR is of particular interest due to its common use as a screening tool. The method showed high DSe (≥0.977) and moderate DSp (0.831) in all 3-populations models. The results further suggest that a follow-up test of serum samples in real-time RT-PCR negative populations may be prudent in cases where epidemiological information suggest a high risk of infection and where a false negative result is of high consequence. This study underlines the need to choose a test appropriate for the purpose of the testing. In the case of a weak positive PCR-result, a follow-up test should be conducted to verify the presence of SAV. Cell culture showed high DSe and DSp and may be used to verify viral presence.

A stochastic network-based model to simulate the spread of pancreas disease (PD) in the Norwegian salmon industry based on the observed vessel movements and seaway distance between marine farms.

Pancreas disease (PD) is a viral disease of economic importance affecting farmed Atlantic salmon (Salmo salar L.) and rainbow trout (Oncorhyncus mykiss (Walbaum)) in the seawater phase in Ireland, Norway and Scotland. In this study we used a stochastic network-based disease spread model to better understand the role of vessel movements and nearby seaway distance on PD spread in marine farms. We used five different edge's definitions and weights for the network construction: high-risk vessel movements, high-risk wellboat movements and high-risk nearby seaway distance at <20 km, <10 km or <5 km, respectively. Models were used to simulate PD spread in marine farms as well as to simulate the spread of marine SAV2 and SAV3 subtypes independently and results were compared with the observed PD, marine SAV2 and SAV3 cases in Norway in 2016. Results revealed that the model that provided the best fit of the observed data and, therefore, the one considered more biologically plausible, was the one using high-risk wellboat movements. The marine SAV2, SAV3 and PD models using wellboat movements were able to correctly simulate the farms status (PD positive or PD negative) with the sensitivity of 84%, 85%, 84% and Specificity of 98%, 97% and 94%, respectively. These results should contribute to inform more cost-effective prevention and control policies to mitigate PD spread and to improve the sustainability and long-term profitability of the salmon industry in Norway.

Risk Factors Associated With Outbreaks of Infectious Salmon Anemia (ISA) With Unknown Source of Infection in Norway.

The occurrence of infectious salmon anemia (ISA) outbreaks in marine farmed Atlantic salmon constitutes a recurring challenge in Norway. Here, we aim to identify risk factors associated with ISA outbreaks with an unknown source of infection (referred to as primary ISA outbreaks). Primary ISA outbreaks are here defined by an earlier published transmission model. We explored a wide range of possible risk factors with logistic regression analysis, trying to explain occurrence of primary ISA with available data from all Norwegian farm sites from 2004 to June 2017. Explanatory variables included site latitude and a range of production and disease data. The mean annual risk of having a primary outbreak of ISA in Norway was 0.7% during this study period. We identified the occurrence of infectious pancreatic necrosis (IPN), having a stocking period longer than 2 months, having the site located at high latitude and high fish density (biomass per cage volume) in the first six months after transfer to sea site as significant risk factors (p < 0.05). We have identified factors related to management routines, other disease problems, and latitude that may help to understand the hitherto unidentified drivers behind the emergence of primary ISA outbreaks. Based on our findings, we also provide management advice that may reduce the incidence of primary ISA outbreaks.

Production impact of influenza A(H1N1)pdm09 virus infection on fattening pigs in Norway.

Newly emerged influenza A(H1N1)pdm09 virus infection in Norwegian pigs, although often observed in a subclinical form, can lower the pig's growth performance by reducing feed efficiency in terms of a poorer feed conversion ratio. Infected pigs would consume more feed and require protracted production time to reach market weight. In our observational longitudinal study, growth performance data from 728 control pigs and 193 infected pigs with known viral shedding time points were analyzed using mixed linear regression models to give estimates of the marginal effects of infection. Gaussian curves describing the variability of the estimates at the individual pig level formed the fundamental inputs to our stochastic models. The models were constructed to simulate the summed negative effects of the infection at the batch level of 150 fattening pigs growing from 33 to 100 kg. Other inputs of variability and uncertainty were 1) batch transmission points, 2) pig infection points to reflect the disease transmission dynamics of the virus, and 3) final prevalence of infected pigs in the batch. Monte Carlo random sampling gave 5,000 estimates on the outputs of the marginal effects for each pig. These results were summed up to provide estimates for a batch size of 150 pigs. This figure was adjusted by our final prevalence distribution function, which was also derived from the longitudinal study with 12 cohorts of infected pigs. For a 150-fattening-pig herd randomly selected from the population, the marginal effects of the infection were 1) 835 kg (fifth percentile) to 1,350 kg (95th percentile) increased feed intake and 2) 194 (fifth percentile) to 334 (95th percentile) pig days in excess of expected figures for an uninfected batch. A batch infected during growth phase 3 (81 to 100 kg BW) gave the worst results since the longitudinal study showed that a pig infected during growth phase 3 required more feed and a greater protracted production time compared to younger infected pigs. Sensitivity analysis showed that final prevalence had the greatest impact on the conditional mean and variation of the marginal effects of infections. Batch transmission point was the next most influential factor. Lowering the final prevalence and preventing older fattening pigs from being infected will have the greatest benefit in saving feed cost and reducing delay in getting the pigs to the market.

Routine clinical inspections in Norwegian marine salmonid sites: A key role in surveillance for freedom from pathogenic viral haemorrhagic septicaemia (VHS).

Since the mid-1980s, clinical inspections of aquaculture sites carried out on a regular basis by authorized veterinarians and fish health biologists (known as fish health services: FHS) have been an essential part of aquatic animal health surveillance in Norway. The aims of the present study were (1) to evaluate the performance of FHS routine clinical inspections for the detection of VHS and (2) to explore the effectiveness of risk-based prioritisation of FHS inspections for demonstrating freedom from VHS in marine salmonid sites in Norway. A stochastic simulation model was developed to estimate site sensitivity (SeS), population sensitivity (SeP), and probability of freedom (PFree). The estimation of SeS takes into consideration the probability that FHS submit samples if a site is infected, the probability that a sample is tested if submitted, the effective probability of infection in fish with clinical signs, laboratory test sensitivity, and the number of tested samples. SeP and PFree were estimated on a monthly basis over a 12 month period for six alternative surveillance scenarios and included the risk factors: region, species, area production density, and biosecurity level. Model results indicate that the current surveillance system, based on routine inspections by the FHS has a high capability for detecting VHS and that there is a high probability of freedom from VHS in Norwegian marine farmed salmonids (PFree >95%). Sensitivity analysis identified the probabilities that samples are submitted and submitted samples are tested, as the most influential input variables. The model provides a supporting tool for evaluation of potential changes in the surveillance strategy, and can be viewed as a platform for similar exotic viral infectious diseases in marine salmonid farming in Norway, if they share similar risk factors.

Adverse effects of Influenza A(H1N1)pdm09 virus infection on growth performance of Norwegian pigs - a longitudinal study at a boar testing station.

BACKGROUND: Influenza A(H1N1)pdm09 virus infection in Norwegian pigs was largely subclinical. This study tested the hypothesis that the infection causes negligible impact on pigs' growth performance in terms of feed conversion efficiency, daily feed intake, daily growth, age on reaching 100 kg bodyweight and overall feed intake. A sample of 1955 pigs originating from 43 breeding herds was classified into five infection status groups; seronegative pigs (n = 887); seropositive pigs (n = 874); pigs positive for virus at bodyweight between 33 kg and 60 kg (n = 123); pigs positive for virus at bodyweight between 61 kg and 80 kg (n = 34) and pigs positive for virus at bodyweight between 81 kg and 100 kg (n = 37). Each pig had daily recordings of feed intake and bodyweight from 33 kg to 100 kg. Marginal effects of the virus infection on the outcomes were estimated by multi-level linear regression, which accounted for known fixed effects (breed, birthdate, average daily feed intake and growth phase) and random effects (cluster effects of pig and herd). RESULTS: The seropositive and virus positive pigs had decreased (P value<0.05) growth performance compared to seronegative pigs even though feed intake was not decreased. Reduced feed conversion efficiency led to lower average daily growth, additional feed requirement and longer time needed to reach the 100 kg bodyweight. The effects were more marked (P value<0.03) in pigs infected at a younger age and lasted a longer period. Despite increased feed intake observed, their growth rates were lower and they took more time to reach 100 kg bodyweight compared to the seronegative pigs. CONCLUSION: Our study rejected the null hypothesis that the virus infection had negligible adverse effects on growth performance of Norwegian pigs.

Expert consultation on risk factors for introduction of infectious pathogens into fish farms.

An expert consultation was conducted to provide quantitative parameters required to inform risk-based surveillance of aquaculture holdings for selected infectious hazards. The hazards were four fish diseases endemic in some or several European countries: infectious salmon anaemia (ISA), viral haemorrhagic septicaemia (VHS), infectious haematopoietic necrosis (IHN), and koi herpes virus disease (KHD). Experts were asked to provide estimates for the relative importance of 5 risk themes for the hazard to be introduced into and infect susceptible fish at the destination. The 5 risk themes were: (1) live fish and egg movements; (2) exposure via water; (3) on-site processing; (4) short distance mechanical transmission and (5) distance independent mechanical transmission. The experts also provided parameter estimates for hazard transmission pathways within the themes. The expert consultation was undertaken in a 2 step approach: an online survey followed by an expert consultation meeting. The expert opinion indicated that live fish movements and exposure via water were the major relevant risk themes. Experts were recruited from several European countries and thus covered a range of farming systems. Therefore, the outputs from the expert consultation have relevance for the European context.

Climate and environmental change drives Ixodes ricinus geographical expansion at the northern range margin.

BACKGROUND: Global environmental change is causing spatial and temporal shifts in the distribution of species and the associated diseases of humans, domesticated animals and wildlife. In the on-going debate on the influence of climate change on vectors and vector-borne diseases, there is a lack of a comprehensive interdisciplinary multi-factorial approach utilizing high quality spatial and temporal data. METHODS: We explored biotic and abiotic factors associated with the latitudinal and altitudinal shifts in the distribution of Ixodes ricinus observed during the last three decades in Norway using antibodies against Anaplasma phagocytophilum in sheep as indicators for tick presence. Samples obtained from 2963 sheep from 90 farms in 3 ecologically different districts during 1978 - 2008 were analysed. We modelled the presence of antibodies against A. phagocytophilum to climatic-, environmental and demographic variables, and abundance of wild cervids and domestic animals, using mixed effect logistic regressions. RESULTS: Significant predictors were large diurnal fluctuations in ground surface temperature, spring precipitation, duration of snow cover, abundance of red deer and farm animals and bush encroachment/ecotones. The length of the growth season, mean temperature and the abundance of roe deer were not significant in the model. CONCLUSIONS: Our results highlight the need to consider climatic variables year-round to disentangle important seasonal variation, climatic threshold changes, climate variability and to consider the broader environmental change, including abiotic and biotic factors. The results offer novel insight in how tick and tick-borne disease distribution might be modified by future climate and environmental change.

Risk factors for cardiomyopathy syndrome (CMS) in Norwegian salmon farming.

Cardiomyopathy syndrome (CMS) has been an economically important disease in Norwegian aquaculture since the 1990s. In this study, data on monthly production characteristics and case registrations were combined in a cohort study and supplemented with a questionnaire-based case-control survey on management factors in order to identify risk factors for CMS. The cohort study included cases and controls from 2005 to 2012. From this dataset differences between all cases and controls were analyzed by a mixed effect multivariate logistic regression. From this we found that the probability of CMS increased with increasing time in the sea, infection pressure, and cohort size, and that cohorts which had previously been diagnosed with heart and skeletal muscle inflammation or which were in farms with a history of CMS in previous cohorts had double the odds of developing CMS. The model was then used to calculate the predicted value for each cohort from which additional data were obtained via the questionnaire-based survey and used as offset for calculating the probability of CMS in a semi-univariate analysis of additional risk factors. Finally, the model was used to calculate the probability of developing CMS in 100 different scenarios in which the cohorts were subject to increasingly worse conditions with regards to the risk factors from the dataset. We believe that this exercise is a good way of communicating the findings to farmers, so they can make informed decisions when trying to avoid CMS in their fish cohorts.

Risk-based methods for fish and terrestrial animal disease surveillance.

Over recent years there have been considerable methodological developments in the field of animal disease surveillance. The principles of risk analysis were conceptually applied to surveillance in order to further develop approaches and tools (scenario tree modelling) to design risk-based surveillance (RBS) programmes. In the terrestrial animal context, examples of risk-based surveillance have demonstrated the substantial potential for cost saving, and a similar benefit is expected also for aquatic animals. RBS approaches are currently largely absent for aquatic animal diseases. A major constraint in developing RBS designs in the aquatic context is the lack of published data to assist in the design of RBS: this applies to data on (i) the relative risk of farm sites becoming infected due to the presence or absence of a given risk factor; (ii) the sensitivity of diagnostic tests (specificity is often addressed by follow-up investigation and re-testing and therefore less of a concern); (iii) data on the variability of prevalence of infection for fish within a holding unit, between holding units and at farm level. Another constraint is that some of the most basic data for planning surveillance are missing, e.g. data on farm location and animal movements. In Europe, registration or authorisation of fish farms has only recently become a requirement under EU Directive 2006/88. Additionally, the definition of the epidemiological unit (at site or area level) in the context of aquaculture is a challenge due to the often high level of connectedness (mainly via water) of aquaculture facilities with the aquatic environment. This paper provides a review of the principles, methods and examples of RBS in terrestrial, farmed and wild animals. It discusses the special challenges associated with surveillance for aquatic animal diseases (e.g. accessibility of animals for inspection and sampling, complexity of rearing systems) and provides an overview of current developments relevant for the design of RBS for fish diseases. Suggestions are provided on how the current constraints to applying RBS to fish diseases can be overcome.

Molecular epidemiology of influenza A (H5N1) viruses, Bangladesh, 2007-2011.

To investigate the origins, evolution and patterns of spread of HPAI H5N1 outbreaks in Bangladesh, we performed a phylogenetic reconstruction analysis using Bayesian methods. The analysis was conducted using 81 hemagglutinin (HA) gene sequences from the H5N1 viruses isolated in Bangladesh from 2007 to 2011, together with 264 publicly available HA sequences of clade 2.2, 2.3.2 and 2.3.4 retrieved from GenBank. Our study provides evidence that clade 2.2.2 viruses that caused outbreaks in Bangladesh were lineages independent from the viruses introduced earlier into India. Furthermore, the Bangladesh clade 2.2.2 descendents subsequently spread to India and Bhutan. This has implications for avian influenza control in southern Asia suggesting multiple routes of entry of the virus including one pathway that spread to neighboring countries via Bangladesh.

Estimation of the reproduction number of salmon pancreas disease virus subtype 3 in homogeneously mixed populations of Norwegian farmed Atlantic salmon.

The reproduction number (R) of salmon pancreas disease (PD) was estimated within homogeneously mixing populations (within-cage) of Norwegian farmed Atlantic salmon (Salmo salar L.) based on data collected during PD epidemics from 10 cages at 2 farming sites. Two approaches were used: (a) estimation of an overall reproduction number (R(cmd)) and a time-dependent reproduction number (R(t)) using mortality records during PD epidemics, and (b) estimating the reproduction number during the early stage of infection (R(sd)) based on data from a surveillance program for SPDV subtype 3. The R(cmd) estimates based on the mortality data ranged from 1.02 to 1.45, and the R(sd) estimates ranged from 1.0 to 2.9. Plots of the R(t) estimates covering the whole epidemic period yielded an increasing slope prior to SPDV3 detection. This study presents a framework for the quantitative measurement of a PD epidemic that could be useful for the evaluation of prevention methods. The time-dependent R(t) estimate can provide an early warning of PD outbreaks.

Influenza A(H1N1)pdm09 virus infection in Norwegian swine herds 2009/10: the risk of human to swine transmission.

Influenza A viruses cause respiratory infection in humans and pigs, and some serotypes can be transmitted between these species. The emergence of influenza A(H1N1)pdm09 virus infections in the spring of 2009 quickly led to a worldwide pandemic in humans, with subsequent introduction of the virus to pig populations. Following a widespread infection in the human population in Norway, influenza A(H1N1)pdm09 virus was introduced to the influenza A naïve Norwegian pig population, and within a few months pigs in more than one third of Norwegian swine herds had antibodies against the virus. A cross-sectional study was performed on all swine nucleus and multiplier herds in Norway to analyze risk factors for introduction of infection, and the preventive effects of recommended biosecurity practices. A surveillance program provided information on infection status of the study herds, and a questionnaire was administered to all 118 nucleus and multiplier herds to collect information on herd variables. The surveillance program revealed that pigs in 42% of the herds had antibodies against influenza A(H1N1)pdm09 virus. The incidence of serologically positive pigs was similar in both multiplier herds (41%) and closed nucleus herds (43%). Multivariable logistic regression showed that presence of farm staff with influenza-like illness (ILI) (OR=4.15, CI 1.5-11.4, p=0.005) and herd size (OR=1.01, CI 1-1.02, p=0.009) were risk factors for infection. The rapid and widespread seroconversion for antibodies against influenza A(H1N1)pdm09 virus in the Norwegian pig population can be explained by the emergence of a novel virus that is readily transmitted between people and swine in a largely susceptible population of humans, and an entirely naïve population of pigs.

Cohort study of effect of vaccination on pancreas disease in Norwegian salmon aquaculture.

Pancreas disease (PD) is an economically important viral disease in Norwegian aquaculture, with 75 to 89 annual outbreaks from 2009 to 2011. To hinder further spread of disease from an initial endemic area on the west coast of Norway, measures for surveillance and control are in place, and the disease is notifiable on a national level. Since 2008, the Norwegian coastline has been divided into 2 administrative zones separated by a production-free area of 10 nautical miles at approximately 63°N. At the same time, a vaccination program involving most marine salmonid farms was initiated by the industry, using a vaccine against PD that was made commercially available in 2007. The effects of the vaccine in the field have been questioned, since the annual number of PD outbreaks has not decreased as expected. However, other production parameters can be used for evaluation of vaccine effect, and in this study the effects of vaccination on cumulative mortality, growth rate, feed conversion factor and number of discarded fish were analyzed using data collected from fish cohorts with and without PD put to sea between spring 2007 and spring 2009. The results show that vaccination against PD has a positive effect in reducing the number of outbreaks, and decreasing cumulative mortality and the number of fish discarded at slaughter.

Risk map and spatial determinants of pancreas disease in the marine phase of Norwegian Atlantic salmon farming sites.

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.