In silico modelling of parasite dynamics

The management of infectious disease is a major concern for conservation of wild fish stocks and is a primary constraint on the viability and sustainability of farmed fish. One pathogen alone, Infectious Salmon Anaemia, is estimated to have cost the Scottish farming industry £20 million in the 1998/1999 outbreak, and still costs the Norwegian and Canadian industries around US$11 and $14 million respectively per annum1. Emerging infectious diseases also pose a serious economic risk to freshwater fisheries, with a number of recently detected pathogens causing large scale disease outbreaks in England and fisheries having to close due these pathogens. By utilizing our new understanding of piscine social networks, we will develop new hydro-environmental models to simulate the fate and transport of parasites. This information is crucial for designing cost-effective control and management mechanisms.
This project will suit either (i) an applied mathematician keen to learn skills in environmental sciences or (ii) a biologist/environmental scientist with strong statistical and computational skills confident that (following suitable training) they will be able to apply cutting-edge statistical methodology (ABC) to the study of piscine parasitology.