Within-farm spread of infectious salmon anemia virus (ISAV) in Atlantic salmon Salmo salar farms in Chile

A Scoping Review on GIS Technologies Applied to Farmed Fish Health Management

Finfish aquaculture, one of the fastest growing intensive sectors worldwide, is threatened by numerous transmissible diseases that may have devastating impacts on its economic sustainability. This review (2010-2022) used a PRISMA extension for scoping reviews and a text mining approach to explore the extent to which geographical information systems (GIS) are used in farmed fish health management and to unveil the main GIS technologies, databases, and functions used to update the spatiotemporal data underpinning risk and predictive models in aquatic surveillance programmes. After filtering for eligibility criteria, the literature search provided 54 records, highlighting the limited use of GIS technologies for disease prevention and control, as well as the prevalence of GIS application in marine salmonid farming, especially for viruses and parasitic diseases typically associated with these species. The text mining generated five main research areas, underlining a limited range of investigated species, rearing environments, and diseases, as well as highlighting the lack of GIS-based methodologies at the core of such publications. This scoping review provides a source of information for future more detailed literature analyses and outcomes to support the development of geospatial disease spread models and expand in-field GIS technologies for the prevention and mitigation of fish disease epidemics.

In silico prediction of B and T cell epitopes of infectious salmon anemia virus proteins and molecular modeling of T cell epitopes to salmon major histocompatibility complex (MHC) class I

Infectious salmon anemia (ISA) can be devastating in farmed Atlantic salmon (Salmo salar). The disease can evolve into epidemics if it is not contained and controlled. ISA epidemics were seen in Norway in the early 1990s and Chile in 2007-2009. Consequently, there is an urgent need to develop a vaccine to prevent or treat the infection. In this study, an immunoinformatic approach was employed to predict 32 lineal B-cell epitopes based on antigenicity and surface accessibility prediction for ISAV fusion (F), hemagglutinin-esterase (HE), and matrix (M) proteins. On the other hand, twelve conformational B-cell epitopes were also predicted. We further identified six antigenic cytotoxic T lymphocyte (CTL) epitopes and investigated the binding interactions with five salmon MHC-I proteins after docking the peptides to the binding groove of the MHC-I proteins. Our results showed that all the predicted epitopes could bind to salmon MHC-I with high negative ΔG values with medium to high binding affinities. Hence, the predicted epitopes have a high potential of being recognized by Atlantic salmon MHC-I to elicit a CD8⁺ T cell response in salmon. The predicted and analyzed B and T cell antigenic epitopes in this work might present an initial set of peptides for future vaccine development against ISAV. The ability to model and predict these interactions will ultimately lead to the ability to predict potential binding for MHCs and epitopes that were not studied previously. As current knowledge of salmon MHC specificity is limited, studying and modeling interactions in the peptide/MHC complex is a key to resolving unknown epitope specificity.

DTU-DADS-Aqua: A simulation framework for modelling waterborne spread of highly infectious pathogens in marine aquaculture

Simulation models are useful tools to predict and elucidate the effects of factors influencing the occurrence and spread of epidemics in animal populations, evaluate the effectiveness of different control strategies and ultimately inform decision-makers about mitigations to reduce risk. There is a paucity of simulation models to study waterborne transmission of viral and bacterial pathogens in marine environments. We developed a stochastic, spatiotemporal hybrid simulation model (DTU-DADS-Aqua) that incorporates a compartmental model for infection spread within net-pens, an agent-based model for infection spread between net-pens within and between sites and uses seaway distance to inform farm-site hydroconnectivity. The model includes processes to simulate infection transmission and control over surveillance, detection and depopulation measures. Different what-if scenarios can be explored according to the input data provided and user-defined parameter values, such as daily surveillance and depopulation capacities or increased animal mortality that triggers diagnostic testing to detect infection. The latter can be easily defined in a software application, in which results are summarized after each simulation. To demonstrate capabilities of the model, we simulated the spread of infectious salmon anaemia virus (ISAv) for realistic scenarios in a transboundary population of farmed Atlantic salmon (Salmo salar L.) in New Brunswick, Canada and Maine, United States. We assessed the progression of infection in the different simulated outbreak scenarios, allowing for variation in the control strategies adopted for ISAv. Model results showed that improved disease detection, coupled with increasing surveillance visits to farm-sites and increased culling capacity for depopulation of infected net-pens reduced the number of infected net-pens and outbreak duration but the number of ISA-infected farm sites was minimally affected. DTU-DADS-Aqua is a flexible modelling framework, which can be applied to study different infectious diseases in the aquatic environment, allowing the incorporation of alternative transmission and control dynamics. The framework is open-source and available at https://github.com/upei-aqua/DTU-DADS-Aqua.

Choosing awareness over fear: Risk analysis and free trade support global food security

Livestock production and global trade are key components to achieving food security, but are bedfellows with the risk for emergence and spread of infectious diseases. The World Trade Organization's Agreement on the Application of Sanitary and Phytosanitary Measures outlines provisions for member countries to protect animal, plant, and public health while promoting free trade. The capacity for risk analysis equips countries to increase access to export markets, improve local animal health and food safety regarding known hazards, and build the institutional capacity to respond to unexpected events. The COVID-19 pandemic has highlighted the need to detect, report, and implement effective response measures to emerging challenges on a local and global scale, and it is crucial that these measures are implemented in a way that supports food production and trade. The use of risk analysis coupled with sound understanding of underlying system dynamics will contribute to resilient and enduring food systems.

Chilean aquaculture and the new challenges: Pathogens, immune response, vaccination and fish diversification

In Chile, the salmon and trout farmed fishing industries have rapidly grown during the last years, becoming one of the most important economic sources for the country. However, infectious diseases caused by bacteria, virus, mycoses and parasites, result in losses of up to 700 million dollars per year for the Chilean aquaculture production with the consequent increase of antibiotic and antiparasitic usage. After 30 years of its first appearance, the main salmon health problem is still the salmonid rickettsial septicaemia (SRS), which together with other disease outbreaks, reveal that vaccines do not provide acceptable levels of long-lasting immune protection in the field. On the other hand, due to the large dependence of the industry on salmonids production, the Chilean government promoted the Aquaculture diversification program by 2009, which includes new species such as Merluccius australis, Cilus gilberti and Genypterus chilensis, however, specific research regarding the immune system and vaccine development are issues that still need to be addressed and must be considered as important as the farm production technologies for new fish species. Based on the experience acquired from the salmonid fish farming, should be mandatory an effort to study the immune system of the new species to develop knowledge for vaccination approaches, aiming to protect these aquaculture species before diseases outbreaks may occur. This review focuses on the current status of the Chilean aquaculture industry, the challenges related to emerging and re-emerging microbial pathogens on salmonid fish farming, and the resulting needs in the development of immune protection by rational designed vaccines. We also discussed about what we have learn from 25 years of salmonid researches and what can be applied to the new Chilean farmed species on immunology and vaccinology.

Molecular features associated with the adaptive evolution of Infectious Salmon Anemia Virus (ISAV) in Chile

Infectious salmon anemia virus (ISAV) is an Orthomyxovirus challenging salmon production, with a particular impact in Chile. During 2007-2010 a devastating and of unexpected consequences epizootic event almost destroyed a blooming industry in the country. The event was caused by an aggressive variant with a distinctive deletion in Segment 6, one of the eight genomic segments of the virus. After the outburst, although the infective viral variant seemed to have disappeared, a non-infective variant, not previously reported, was discovered and is characterized by a complete, non-deleted coding segment 6, which has prevailed in the fish population until now. This variant, known as HPR0, appears to be the ancestor strain of ISAV from which novel infective variants are generated. Additional variations in segment 5 have also been associated with the virulence observed in the field, an analysis of the differences in these two protein coding segments has been performed. It appears to us that a combinatorial effect exists between the features displayed by segments 5 and 6 which modulate the intensity of viral outbursts. As a result, a theoretical integrative model is presented which explains the different degree of virulence observed in the field based only on molecular data, this could help estimating the intensity of damage a given variant might exert over a productive farm.

Connectivity-based risk ranking of infectious salmon anaemia virus (ISAv) outbreaks for targeted surveillance planning in Canada and the USA

Infectious salmon anaemia (ISA) can be a serious viral disease of farmed Atlantic salmon (Salmo salar). A tool to rank susceptible farms based on the risk of ISA virus (ISAv) infection spread from infectious farms after initial incursion or re-occurrence in an endemic area, can help guide monitoring and surveillance activities. Such a tool could also support the response strategy to contain virus spread, given available resources. We developed a tool to rank ISAv infection risks using seaway distance and hydrodynamic information separately and combined. The models were validated using 2002-2004 ISAv outbreak data for 30 farms (24 in New Brunswick, Canada and 6 in Maine, United States). Time sequence of infection spread was determined from the outbreak data that included monthly infection status of the cages on these farms. The first infected farm was considered as the index site for potential spread of ISAv to all other farms. To assess the risk of ISAv spreading to susceptible farms, the second and subsequent infected farms were identified using the farm status in the given time period and all infected farms from the previous time periods. Using the three models (hydrodynamic only, seaway-distance, and combined hydrodynamic-seaway-distance based models), we ranked susceptible farms within each time interval by adding the transmission risks from surrounding infected farms and sorting them from highest to lowest. To explore the potential efficiency of targeted sampling, we converted rankings to percentiles and assessed the model's predictive performance by comparing farms identified as high risk based on the rank with those that were infected during the next time interval as observed in the outbreak data. The overall predictive ability of the models was compared using area under the ROC curve (AUC). Farms that become infected in the next period were always within the top 65% of the rank predicted by our models. The overall predictive ability of the combined (hydrodynamic-seaway-distance based model) model (AUC = 0.833) was similar to the model that only used seaway distance (AUC = 0.827). Such models can aid in effective surveillance planning by balancing coverage (number of farms included in surveillance) against the desired level of confidence of including all farms that become infected in the next time period. Our results suggest that 100% of the farms that become infected in the next time period could be targeted in a surveillance program, although at a significant cost of including many false positives.