Simulating blood fluke, Cardicola forsteri, infection in farmed southern bluefin tuna, Thunnus maccoyii, using stochastic models

a b s t r a c t Article history: Received 28 August 2007 Received in revised form 12 April 2009 Accepted 23 April 2009 Keywords: Sanguinicolidae Thunnus Aquaculture Stochastic Epidemiology Two stochastic models were developed to describe the infection pattern of Cardicola forsteri in farmed southern bluefin tuna, Thunnus maccoyii. Observed field data on the lengths of flukes over a growout season were used as the basis for the models and biological data from C. forsteri and other blood flukes infecting fish were used as parameters. Monte Carlo sampling techniques were used in the simulations. The first model simulated the lengths of fluke according to the month when they were sampled. The output of this model was then compared to the observed field data. A second model was developed to determine stochastically the age of the observed fluke using their lengths. The output of the first model was shown to be similar to the observed lengths of the flukes. An estimated time of infection was produced from the second model and it was shown that there were two major infection events early in the growout season that contributed to the majority of infections by C. forsteri. These peaks of infection were shown to occur at 14 days (S.D.=10.2) and 55 days (S.D.=10.1) post-transfer. Stochastic modeling has not been used before to describe the infection period of a helminth in cultured fish, and was shown to be useful here. © 2009 Elsevier B.V. All rights reserved