Ranking freshwater fish farms for the risk of pathogen introduction and spread

Prevalence of genetically similar Flavobacterium columnare phages across aquaculture environments reveals a strong potential for pathogen control

Intensive aquaculture conditions expose fish to bacterial infections, leading to significant financial losses, extensive antibiotic use and risk of antibiotic resistance in target bacteria. Flavobacterium columnare causes columnaris disease in aquaculture worldwide. To develop a bacteriophage‐based control of columnaris disease, we isolated and characterized 126 F. columnare strains and 63 phages against F. columnare from Finland and Sweden in 2017. Bacterial isolates were virulent on rainbow trout (Oncorhynchus mykiss) and fell into four previously described genetic groups A, C, E and G, with genetic groups C and E being the most virulent. Phage host range studied against a collection of 227 bacterial isolates (from 2013 to 2017) demonstrated modular infection patterns based on host genetic group. Phages infected contemporary and previously isolated bacterial hosts, but bacteria isolated most recently were generally resistant to previously isolated phages. Despite large differences in geographical origin, isolation year or host range of the phages, whole‐genome sequencing of 56 phages showed high level of genetic similarity to previously isolated F. columnare phages (Ficleduovirus, Myoviridae). Altogether, this phage collection demonstrates a potential for use in phage therapy.

Comparative assessment of live cyprinid and salmonid movement networks in England and Wales

Disease poses a significant threat to aquaculture. While there are a number of factors contributing to pathogen transmission risk, movement of live fish is considered the most important. Understanding live fish movement patterns for different aquaculture sectors is therefore crucial to predicting disease occurrence and necessary for the development of effective, risk-based biosecurity, surveillance and containment policies. However, despite this, our understanding of live movement patterns of key aquaculture species, namely salmonids and cyprinids, within England and Wales remains limited. In this study, networks reflecting live fish movements associated with the cyprinid and salmonid sectors in England and Wales were constructed. The structure, composition and key attributes of each network were examined and compared to provide insight into the nature of trading patterns and connectedness, as well as highlight sites at a high risk of spreading disease. Connectivity at both site and catchment level was considered to facilitate understanding at different resolutions, providing further insight into disease outbreaks, with industry wide implications. The study highlighted that connectivity through live fish movements was extensive for both industries. The salmonid and cyprinid networks comprised 2533 and 3645 nodes, with a network density of 5.81 × 10^-4 and 4.2 × 10^-4, respectively. The maximum network reach of 2392 in the salmonid network was higher, both in absolute terms and as a proportion of the overall network, compared to maximum network reach of 2085 in the cyprinid network. However, in contrast, the number of sites in the cyprinid network with a network reach greater than one was 513, compared to 171 in the salmonid network. Patterns of connectivity indicated potential for more frequent yet smaller scale disease outbreaks in the cyprinid industry and less frequent but larger scale outbreaks in the salmonid industry. Further, high connectivity between river catchments within both networks was shown, posing challenges for zoning at the catchment level for the purpose of disease management. In addition to providing insight into pathogen transmission and epidemic potential within the salmonid and cyprinid networks, the study highlights the utility of network analysis, and the value of accessible, accurate live fish movement data in this context. The application of outputs from this study, and network analysis methodology, to inform future disease surveillance and control policies, both within England and Wales and more broadly, is discussed.

Data-Driven Network Modeling as a Framework to Evaluate the Transmission of Piscine Myocarditis Virus (PMCV) in the Irish Farmed Atlantic Salmon Population and the Impact of Different Mitigation Measures

Cardiomyopathy syndrome (CMS) is a severe cardiac disease of Atlantic salmon caused by the piscine myocarditis virus (PMCV), which was first reported in Ireland in 2012. In this paper, we describe the use of data-driven network modeling as a framework to evaluate the transmission of PMCV in the Irish farmed Atlantic salmon population and the impact of different mitigation measures. Input data included live fish movement data from 2009 to 2017, population dynamics events and the spatial location of the farms. With these inputs, we fitted a network-based stochastic infection spread model. After assumed initial introduction of the agent in 2009, our results indicate that it took 5 years to reach a between-farm prevalence of 100% in late 2014, with older fish being most affected. Local spread accounted for only a small proportion of new infections, being more important for sustained infection in a given area. Spread via movement of subclinically infected fish was most important for explaining the observed countrywide spread of the agent. Of the targeted intervention strategies evaluated, the most effective were those that target those fish farms in Ireland that can be considered the most connected, based on the number of farm-to-farm linkages in a specific time period through outward fish movements. The application of these interventions in a proactive way (before the first reported outbreak of the disease in 2012), assuming an active testing of fish consignments to and from the top 8 ranked farms in terms of outward fish movement, would have yielded the most protection for the Irish salmon farming industry. Using this approach, the between-farm PMCV prevalence never exceeded 20% throughout the simulation time (as opposed to the simulated 100% when no interventions are applied). We argue that the Irish salmon farming industry would benefit from this approach in the future, as it would help in early detection and prevention of the spread of viral agents currently exotic to the country.

Can biosecurity and local network properties predict pathogen species richness in the salmonid industry?

Salmonid farming in Ireland is mostly organic, which implies limited disease treatment options. This highlights the importance of biosecurity for preventing the introduction and spread of infectious agents. Similarly, the effect of local network properties on infection spread processes has rarely been evaluated. In this paper, we characterized the biosecurity of salmonid farms in Ireland using a survey, and then developed a score for benchmarking the disease risk of salmonid farms. The usefulness and validity of this score, together with farm indegree (dichotomized as ≤ 1 or > 1), were assessed through generalized Poisson regression models, in which the modeled outcome was pathogen richness, defined here as the number of different diseases affecting a farm during a year. Seawater salmon (SW salmon) farms had the highest biosecurity scores with a median (interquartile range) of 82.3 (5.4), followed by freshwater salmon (FW salmon) with 75.2 (8.2), and freshwater trout (FW trout) farms with 74.8 (4.5). For FW salmon and trout farms, the top ranked model (in terms of leave-one-out information criteria, looic) was the null model (looic = 46.1). For SW salmon farms, the best ranking model was the full model with both predictors and their interaction (looic = 33.3). Farms with a higher biosecurity score were associated with lower pathogen richness, and farms with indegree > 1 (i.e. more than one fish supplier) were associated with increased pathogen richness. The effect of the interaction between these variables was also important, showing an antagonistic effect. This would indicate that biosecurity effectiveness is achieved through a broader perspective on the subject, which includes a minimization in the number of suppliers and hence in the possibilities for infection to enter a farm. The work presented here could be used to elaborate indicators of a farm’s disease risk based on its biosecurity score and indegree, to inform risk-based disease surveillance and control strategies for private and public stakeholders.

Validation of a model for ranking aquaculture facilities for risk-based disease surveillance

A semi-quantitative model for risk ranking of aquaculture facilities in Switzerland with regard to the introduction and spread of Viral Haemorrhagic Septicaemia (VHS) and Infectious Haematopoietic Necrosis (IHN) was developed in a previous study (Diserens et al., 2013). The objective of the present study was to validate this model using data collected during field visits on aquaculture sites in four Swiss cantons compared to data collected through a questionnaire in the previous study. A discrepancy between the values obtained with the two different methods was found in 32.8% of the parameters, resulting in a significant difference (p<0.001) in the risk classification of the facilities. As data gathered exclusively by means of a questionnaire are not of sufficient quality to perform a risk-based surveillance of aquaculture facilities a combination of questionnaires and farm inspections is proposed. A web-based reporting system could be advantageous for the factors which were identified as being more likely to vary over time, in particular for factors considering fish movements, which showed a marginally significant difference in their risk scores (p≥0.1) within a six- month period. Nevertheless, the model proved to be stable over the considered period of time as no substantial fluctuations in the risk categorisation were observed (Kappa agreement of 0.77).Finally, the model proved to be suitable to deliver a reliable risk ranking of Swiss aquaculture facilities according to their risk of getting infected with or spreading of VHS and IHN, as the five facilities that tested positive for these diseases in the last ten years were ranked as medium or high risk. Moreover, because the seven fish farms that were infected with Infectious Pancreatic Necrosis (IPN) during the same period also belonged to the risk categories medium and high, the classification appeared to correlate with the occurrence of this third viral fish disease.

Current status of parasitic ciliates Chilodonella spp. (Phyllopharyngea: Chilodonellidae) in freshwater fish aquaculture

Freshwater fish farming contributes to more than two-thirds of global aquaculture production. Parasitic ciliates are one of the largest causes of production loss in freshwater farmed fishes, with species from the genus Chilodonella being particularly problematic. While Chilodonella spp. include 'free-living' fauna, some species are involved in mortality events of fish, particularly in high-density aquaculture. Indeed, chilodonellosis causes major productivity losses in over 16 species of farmed freshwater fishes in more than 14 countries. Traditionally, Chilodonella species are identified based on morphological features; however, the genus comprises yet uncharacterized cryptic species, which indicates the necessity for molecular diagnostic methods. This review synthesizes current knowledge on the biology, ecology and geographic distribution of harmful Chilodonella spp. and examines pathological signs, diagnostic methods and treatments. Recent advances in molecular diagnostics and the ability to culture Chilodonella spp. in vitro will enable the development of preventative management practices and sustained freshwater fish aquaculture production.

Production of red tilapia (Oreochromis spp.) in floating cages in the Mekong Delta, Vietnam: mortality and health management

The Mekong Delta in Vietnam is one of the most productive aquaculture regions in the world, in which the red tilapia (Oreochromis spp.) industry is a small-scale industry that mainly supplies local markets in the delta region. Little is known about the frequency of mortality events and health management in this sector. We describe red tilapia floating cage production systems in the Mekong Delta, Vietnam, for the purposes of quantifying mortality and associated production factors, and describing practices that may influence pathogen introduction and spread to and from farms. In July 2014, approximately 50 red tilapia farmers from 4 provinces (201 farmers in total) were randomly selected and interviewed. Median overall perceived mortality (PM) within a production cycle was 35%. Overall PM was found to be affected by province (p < 0.01), age of farmers (p = 0.01), anticipated main reason for PM in the first 2 wk (p = 0.03), most common market for the fish (p = 0.02), and whether farmers recorded stocking information (p = 0.01). Based on the interviews, we describe and discuss processes that potentially affect pathogen introduction and spread on these farms, such as movements of live and dead fish, distances between farms, mechanical transmission, and biosecurity practices such as treating fish before stocking, using disinfectants, and sharing equipment, and harvesters' movements. This study provides fundamental understanding of red tilapia aquaculture management in the Mekong Delta, and describes management factors that could become important in the event of disease outbreaks.

Molecular Evolution and Phylogeography of Co-circulating IHNV and VHSV in Italy

Infectious haematopoietic necrosis virus (IHNV) and viral haemorrhagic septicaemia virus (VHSV) are the most important viral pathogens impacting rainbow trout farming. These viruses are persistent in Italy, where they are responsible for severe disease outbreaks (epizootics) that affect the profitability of the trout industry. Despite the importance of IHNV and VHSV, little is known about their evolution at a local scale, although this is likely to be important for virus eradication and control. To address this issue we performed a detailed molecular evolutionary and epidemiological analysis of IHNV and VHSV in trout farms from northern Italy. Full-length glycoprotein gene sequences of a selection of VHSV (n = 108) and IHNV (n = 89) strains were obtained. This revealed that Italian VHSV strains belong to sublineages Ia1 and Ia2 of genotype Ia and are distributed into 7 genetic clusters. In contrast, all Italian IHNV isolates fell within genogroup E, for which only a single genetic cluster was identified. More striking was that IHNV has evolved more rapidly than VHSV (mean rates of 11 and 7.3 × 10⁻⁴ nucleotide substitutions per site, per year, respectively), indicating that these viruses exhibit fundamentally different evolutionary dynamics. The time to the most recent common ancestor of both IHNV and VHSV was consistent with the first reports of these pathogens in Italy. By combining sequence data with epidemiological information it was possible to identify different patterns of virus spread among trout farms, in which adjacent facilities can be infected by either genetically similar or different viruses, and farms located in different water catchments can be infected by identical strains. Overall, these findings highlight the importance of combining molecular and epidemiological information to identify the determinants of IHN and VHS spread, and to provide data that is central to future surveillance strategies and possibly control.

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.

Expert Opinion on the Perceived Effectiveness and Importance of On-Farm Biosecurity Measures for Cattle and Swine Farms in Switzerland

Biosecurity is crucial for safeguarding livestock from infectious diseases. Despite the plethora of biosecurity recommendations, published scientific evidence on the effectiveness of individual biosecurity measures is limited. The objective of this study was to assess the perception of Swiss experts about the effectiveness and importance of individual on-farm biosecurity measures for cattle and swine farms (31 and 30 measures, respectively). Using a modified Delphi method, 16 Swiss livestock disease specialists (8 for each species) were interviewed. The experts were asked to rank biosecurity measures that were written on cards, by allocating a score from 0 (lowest) to 5 (highest). Experts ranked biosecurity measures based on their importance related to Swiss legislation, feasibility, as well as the effort required for implementation and the benefit of each biosecurity measure. The experts also ranked biosecurity measures based on their effectiveness in preventing an infectious agent from entering and spreading on a farm, solely based on transmission characteristics of specific pathogens. The pathogens considered by cattle experts were those causing Bluetongue (BT), Bovine Viral Diarrhea (BVD), Foot and Mouth Disease (FMD) and Infectious Bovine Rhinotracheitis (IBR). Swine experts expressed their opinion on the pathogens causing African Swine Fever (ASF), Enzootic Pneumonia (EP), Porcine Reproductive and Respiratory Syndrome (PRRS), as well as FMD. For cattle farms, biosecurity measures that improve disease awareness of farmers were ranked as both most important and most effective. For swine farms, the most important and effective measures identified were those related to animal movements. Among all single measures evaluated, education of farmers was perceived by the experts to be the most important and effective for protecting both Swiss cattle and swine farms from disease. The findings of this study provide an important basis for recommendation to farmers and policy makers.

The Assessment of African Swine Fever Virus Risk to Belgium Early 2014, using the Quick and Semiquantitative Pandora Screening Protocol

A risk assessment was organized during the early EU ASF outbreaks of early 2014 (February-April) and performed in cooperation with 15 Belgian and European experts on ASFV and its epidemiology in pigs/wild boar. African swine fever (ASF) is considered as one of the most dangerous infectious pig diseases, causing many outbreaks. Since the end of 2013 - early 2014, several outbreaks within the European Union (Lithuania, Poland, Estonia and Latvia) were reported to OIE, which prompted several risk assessments by (inter)national bodies and scientists. In this study, the open source, semiquantitative Pandora risk assessment tool was used for a quick overall screening of the risk posed by ASF to Belgium early 2014. A set of integrated risk scores was calculated within the Pandora framework. Experts scored the questions and uncertainty levels in the Pandora modules individually, after which the calculations were performed and averaged scores were used within pre-defined risk scales to define and visualize the ASF risk to Belgium. Emergence risk was considered low (Pandora score 0.29), while disease consequences were deemed high (0.93); the resulting multiplicative overall risk of ASFV for Belgium was low (0.27). The Belgian experts tended to give lower risk scores than the European experts, especially for entry risk and trade/public opinion consequences. These risk scores are further interpreted with a due consideration of the qualitative data in the expert remarks and of other ASF risk assessments. The results are similar to more extensive and elaborate risk assessment models/procedures which may require more time and resources. The Pandora tool allows sequential updates to monitor (rates of) increasing risk and provides information for risk managers to organize targeted control.

Spatio-temporal risk factors for viral haemorrhagic septicaemia (VHS) in Danish aquaculture

Viral haemorrhagic septicaemia (VHS) is an economically very important fish disease in the northern hemisphere. When the VHS virus was first isolated in Denmark 50 yr ago, more than 80% of the 800 Danish fish farms were considered to be infected, but vigilant surveillance and eradication programmes led to a drastic reduction in prevalence, and finally, to complete eradication of VHS. Denmark thus obtained official status as an approved VHS-free member state within the European Union in November 2013. Data on outbreaks within the country have been collected since 1970, and here we combined these data with the geographical coordinates of fish farms to identify clusters of high disease prevalence and other risk factors. Our analyses revealed a statistically significant cluster in the southwestern part of the country, which persisted throughout the study period. Being situated within such a cluster was a significant risk factor for VHS. For freshwater rainbow trout farms situated inland, the number of upstream farms was a determining risk factor for VHS, as was distance to the nearest VHS-infected farm and year. Whether the farm used fresh or marine water in production did not have any influence on the risk of VHS, when accounting for whether the farm was situated inside a cluster of high risk. This information can be used when implementing risk-based surveillance programmes.

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.

Integrating expert judgment in veterinary epidemiology: example guidance for disease freedom surveillance

Expert opinions supplement empirical data in many epidemiologic assessments. For veterinary disease freedom surveillance, where the geographic scope of concern is often broad, populations subject to change, decisions eminent and empirical data, expert opinion can be a critical component of the decision making process. However, opinion is by definition subjective and the manner in which opinion is sought can impact the quality and reliability of estimates. Group interaction can hinder or improve the estimation process, depending on its facilitation. Further, whether and how validation is conducted can limit or increase acceptance of the resulting model. While the utility of expert opinion is widely recognized in many fields, and the impact of its use or misuse implicit, standards for application to veterinary assessments are not readily available. This paper aims to foster discussion on this influential component of epidemiology, with disease freedom application as a focus. Benefits and concerns attributed to expert judgment and guidelines for its structured elicitation are described, borrowing insights from its long history of use in decision science fields and examples from recent veterinary assessments.