Aquatic animal diseases cause high mortality, threatening biodiversity, and food security, resulting in substantial economic impact to aquaculture and recreational fishing industries. Tools such as mathematical models and computer simulations are valuable for predicting the potential spread and impact of disease, thereby informing evidence-based, cost-effective management policy and decision making.
The AquaNet-Mod is a modelling tool used to simulate the spread of disease across a network of connected sites representing the aquaculture industry, in this case the trout aquaculture and inland fishery industry in England and Wales. Each site is considered a single epidemiological unit, and disease can spread between sites via four transmission mechanisms: live fish movements, river-based transmission, short distance mechanical transmission and distance independent mechanical transmission. The connectivity between sites is based upon real-world data gathered as part of the Competent Authority’s statutory monitoring. Following the seeding of infection, sites transit between three disease states: susceptible, clinically infected and sub clinically infected, according to defined criteria. Disease spread can be interrupted by the application of disease mitigation measures and controls such as contact tracing, culling, fallowing and surveillance. The model also incorporates economic costs to affected sites and the Competent Authority associated with infection and controls, allowing the cost of an outbreak to be estimated and compared between control scenarios.
Here we present AquaNet-Mod outputs for Viral Haemorrhagic Septicaemia (VHS), a freshwater salmonid disease listed by WOAH and in the UK. Simulations showed that, intuitively, controls which reduced the total number of infected sites reduced the overall epidemic costs. In particular, the model demonstrated that the current disease controls in England and Wales resulted in the lowest total number of infected sites, on average, and that contact tracing was both effective at reducing the spread of disease through the network and relatively low cost. The merit of this model for evaluation of disease spread and the cost-effectiveness of controls, in the context of policy, is discussed.