Epidemics and control strategies for diseases of farmed salmonids: a parameter study

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.

The aquaculture disease network model (AquaNet-Mod): A simulation model to evaluate disease spread and controls for the salmonid industry in England and Wales

Infectious disease causes significant mortality in wild and farmed systems, threatening biodiversity, conservation and animal welfare, as well as food security. To mitigate impacts and inform policy, tools such as mathematical models and computer simulations are valuable for predicting the potential spread and impact of disease. This paper describes the development of the Aquaculture Disease Network Model, AquaNet-Mod, and demonstrates its application to evaluating disease epidemics and the efficacy of control, using a Viral Haemorrhagic Septicaemia (VHS) case study. AquaNet-Mod is a data-driven, stochastic, state-transition model. Disease spread can occur via four different mechanisms, i) live fish movement, ii) river based, iii) short distance mechanical and iv) distance independent mechanical. Sites transit between three disease states: susceptible, clinically infected and subclinically infected. Disease spread can be interrupted by the application of disease mitigation measures and controls such as contact tracing, culling, fallowing and surveillance. Results from a VHS case study highlight the potential for VHS to spread to 96% of sites over a 10 year time horizon if no disease controls are applied. Epidemiological impact is significantly reduced when live fish movement restrictions are placed on the most connected sites and further still, when disease controls, representative of current disease control policy in England and Wales, are applied. The importance of specific disease control measures, particularly contact tracing and disease detection rate, are also highlighted. The merit of this model for evaluation of disease spread and the efficacy of controls, in the context of policy, along with potential for further application and development of the model, for example to include economic parameters, is discussed.

Quantifying the impact of temperature variation on birnavirus transmission dynamics in hard clams Meretrix lusoria

Susceptibility of hard clams Meretrix lusoria to birnavirus (BV) infections caused by temperature variations, from a mechanistic perspective, has rarely been explored. We used a deterministic susceptible-infectious-mortality (SIM) model to derive temperature-dependent key epidemiologic parameters based on data sets of viral infections in hard clams subjected to acute temperature changes. To parameterize seasonal pattern dependence, we estimated monthly based cumulative mortality and basic reproduction numbers (R₀ ) between 1997 and 2017 by way of statistical analysis. Two alternative disease control models were also proposed to assess status of controlled temperature-mediated BV infection by using, respectively, control reproduction number (R_C )-control line criterion and removal strategy-based control measure. We showed that based on R_C -control strategy, when temperatures ranged from 15 to 26.8°C, proportion of susceptible hard clams removed should be at least 0.22%. Based on removal-control strategy, we found that by limiting pond water temperature to 25-30°C, together with increased removal rates and periods to remove hard clams, it is better to remove hard clams from June and August to reduce both mortality rate and spread of BV. Our results can be used to monitor BV transmission potential in hard clams that will contribute to government control strategy to eradicate future BV epidemics.

The contact structure of Great Britain's salmon and trout aquaculture industry

•

87% of English and Welsh nodes are reachable from Scotland via the live fish movement network.

•

72% of Scottish nodes are reachable from England or Wales via the live fish movement network.

•

7.2% of all live fish movements cross the England-Scotland border.

•

Targeted surveillance on a handful of sites is effective in identifying and controlling outbreaks.

•

The combination of different mechanisms of transmission increases the chance of large epidemics.

We analyse the network structure of the British salmonid aquaculture industry from the perspective of infectious disease control. We combine for the first time live fish transport (or movement) data covering England and Wales with data covering Scotland and include network layers representing potential transmission by rivers, sea water and local transmission via human or animal vectors in the immediate vicinity of each farm or fishery site. We find that 7.2% of all live fish transports cross the England-Scotland border and network analysis shows that 87% of English and Welsh nodes and 72% of Scottish nodes are reachable from cross-border connections via live fish transports alone. Consequently, from a disease-control perspective, the contact structures of England and Wales and of Scotland should not be considered in isolation. We also show that large epidemics require the live fish movement network and so control strategies targeting movements can be very effective. While there is relatively low risk of widespread epidemics on the live fish transport network alone, the potential risk is substantially amplified by the combined interaction of multiple network layers.

Assessing the population transmission dynamics of tilapia lake virus in farmed tilapia

A novel virus, tilapia lake virus (TiLV), has been identified as a key pathogen responsible for disease outbreak and mass mortality of farmed tilapia. We used a deterministic susceptible-infectious-mortality (SIM) model to derive key disease information appraised with published TiLV-induced cumulative mortality data. The relationship between tilapia mortality and TiLV exposure dosages was described by the Hill model. Furthermore, a disease control model was proposed to determine the status of controlled TiLV infection using a parsimonious control reproduction number (R_C )-control line criterion. Results showed that the key disease determinants of transmission rate and basic reproduction number (R₀ ) could be derived. The median R₀ estimate was 2.59 in a cohabitation setting with 2.6 × 10⁵  TCID50 fish^-1 TiLV. The present R_C -control model can be employed to determine whether TiLV containment is feasible in an outbreak farm by quantifying the current level of transmission. The SIM model can then be applied to predict what additional control is required to manage R_C  < 1. We offer valuable tools for aquaculture engineers and public health scientists the mechanistic-based assessment that allows a more rigorous evaluation of different control strategies to reduce waterborne diseases in aquaculture farming systems.

Characterization of the live salmonid movement network in Ireland: Implications for disease prevention and control

Live fish movement is considered as having an important role in the transmission of infectious diseases. For that reason, interventions for cost-effective disease prevention and control rely on a sound understanding of the patterns of live fish movements in a region or country. Here, we characterize the network of live fish movements in the Irish salmonid farming industry during 2013, using social network analysis and spatial epidemiology methods, and identify interventions to limit the risk of disease introduction and spread. In the network there were 62 sites sending and/or receiving fish, with a total of 130 shipments (84 arcs) comprising approx. 17.2 million fish during the year. Atlantic salmon shipments covered longer distances than trout shipments, with some traversing the entire country. The average shipment of Atlantic salmon was 146,186 (SD 194,344) fish, compared to 77,928 (127,009) for trout, however, variability was high. There were 3 periods where shipments peaked (February-April, June-September, and November), which were related to specific stages of fish. The network was disconnected and had two major weak components, the first one with 39 nodes (mostly Atlantic salmon sites), and the second one with 10 nodes (exclusively trout sites). Correlation between in and out-degree at each site and assortativity coefficient were slightly low and non-significant: -0.08 (95% CI: -0.22, 0.06) and -0.13 (95% CI: -0.36, 0.08), respectively, indicating random mixing with regard to node degree. Although competing models also produced a good fit to degree distribution, it is likely that the network possesses both small-world and scale-free topology. This would facilitate the spread and persistence of infection in the salmon production system, but would also facilitate the design of risk-based surveillance strategies by targeting hubs, bridges or cut-points. Using Infomap community detection algorithms, 2 major communities were identified within the giant weak component, which were linked by only 4 nodes. Communities found had no correspondence with geographical zones within the country, which could potentially hinder the implementation of zoning strategies for disease control and eradication. Three significant spatial clusters of node centrality measures were detected, two in county Donegal (betweenness and outcloseness) and one in county Galway (incloseness), highlighting the importance of these locations as hot spots of highly central sites with a higher potential for both introduction and spread of infection. These results will assist in the design and implementation of measures to reduce the sanitary risks emerging from live fish trade within Ireland.

Seasonal increase in sea temperature triggers pancreas disease outbreaks in Norwegian salmon farms

Pancreas disease (PD) is a viral disease causing negative impacts on economy of salmon farms and fish welfare. Its transmission route is horizontal, and water transport by ocean currents is an important factor for transmission. In this study, the effect of temperature changes on PD dynamics in the field has been analysed for the first time. To identify the potential time of exposure to the virus causing PD, a hydrodynamic current model was used. A cohort of salmon was assumed to be infected the month it was exposed to virus from other infective cohorts by estimated water contact. The number of months from exposure to outbreak defined the incubation period, which was used in this investigation to explore the relationship between temperature changes and PD dynamics. The time of outbreak was identified by peak in mortality based on monthly records from active sites. Survival analysis demonstrated that cohorts exposed to virus at decreasing sea temperature had a significantly longer incubation period than cohorts infected when the sea temperature was increasing. Hydrodynamic models can provide information on the risk of being exposed to pathogens from neighbouring farms. With the knowledge of temperature-dependent outbreak probability, the farmers can emphasize prophylactic management, avoid stressful operations until the sea temperature is decreasing and consider removal of cohorts at risk, if possible.

Modelling management strategies for a disease including undetected sub-clinical infection: bacterial kidney disease in Scottish salmon and trout farms

Disease is a major constraint on animal production and welfare in agriculture and aquaculture. Movement of animals between farms is one of the most significant routes of disease transmission and is particularly hard to control for pathogens with subclinical infection. Renibacterium salmoninarum causes bacterial kidney disease (BKD) in salmonid fish, but infection is often sub-clinical and may go undetected with major potential implications for disease control programmes. A Susceptible-Infected model of R. salmoninarum in Scottish aquaculture has been developed that subdivides the infected phase between known and undetected sub-clinically infected farms and diseased farms whose status is assumed to be known. Farms officially known to be infected are subject to movement controls restricting spread of infection. Model results are sensitive to prevalence of undetected infection, which is unknown. However, the modelling suggests that controls that reduce BKD prevalence include improve biosecurity on farms, including those not known to be infected, and improved detection of infection. Culling appears of little value for BKD control. BKD prevalence for rainbow trout farms is less sensitive to controls than it is for Atlantic salmon farms and so different management strategies may be required for the sectors.

Seasonality and heterogeneity of live fish movements in Scottish fish farms

Movement of live animals is a key contributor to disease spread. Farmed Atlantic salmon Salmo salar, rainbow trout Onchorynchus mykiss and brown/sea trout Salmo trutta are initially raised in freshwater (FW) farms; all the salmon and some of the trout are subsequently moved to seawater (SW) farms. Frequently, fish are moved between farms during their FW stage and sometimes during their SW stage. Seasonality and differences in contact patterns across production phases have been shown to influence the course of an epidemic in livestock; however, these parameters have not been included in previous network models studying disease transmission in salmonids. In Scotland, farmers are required to register fish movements onto and off their farms; these records were used in the present study to investigate seasonality and heterogeneity of movements for each production phase separately for farmed salmon, rainbow trout and brown/sea trout. Salmon FW-FW and FW-SW movements showed a higher degree of heterogeneity in number of contacts and different seasonal patterns compared with SW-SW movements. FW-FW movements peaked from May to July and FW-SW movements peaked from March to April and from October to November. Salmon SW-SW movements occurred more consistently over the year and showed fewer connections and number of repeated connections between farms. Therefore, the salmon SW-SW network might be treated as homogeneous regarding the number of connections between farms and without seasonality. However, seasonality and production phase should be included in simulation models concerning FW-FW and FW-SW movements specifically. The number of rainbow trout FW-FW and brown/sea trout FW-FW movements were different from random. However, movements from other production phases were too low to discern a seasonal pattern or differences in contact pattern.