Evaluation of a British computer model to simulate gastrointestinal nematodes in sheep on Canadian farms

• Published in: Veterinary parasitology 2010-11, Vol.174 (1), p.92-105
• Main Authors: Guthrie, A.D., Learmount, J., VanLeeuwen, J., Peregrine, A.S., Kelton, D., Menzies, P.I., Fernández, S., Martin, R.C., Mederos, A., Taylor, M.A.
• Format: Article
• Language: English
• Subjects: Animals; Canada; computer analysis; Computer Simulation; epidemiology; ewes; fecal egg count; gastrointestinal nematodes; Gastrointestinal parasites; Gastrointestinal Tract - parasitology; lambs; Models, Biological; Nematoda - physiology; nematode infections; Nematode Infections - veterinary; Parasite Egg Count; Parasite management; Regression Analysis; Reproducibility of Results; Sheep; sheep diseases; Sheep Diseases - epidemiology; Simulation modelling; simulation models
• ISSN: 0304-4017; 1873-2550
• DOI: 10.1016/j.vetpar.2010.08.002

With increasing levels of anthelmintic resistance worldwide and a growing demand to produce more organic products, utilisation of control strategies for gastrointestinal nematodes (GIN) that minimize the use of anthelmintics becomes even more important. This study evaluated the farm-level performance of an existing predictive sheep parasite model from the United Kingdom (UK), using Canadian data. The UK model simulates the epidemiology of three major GIN species of interest ( Teladorsagia spp., Haemonchus spp. and Trichostrongylus spp.) and provides a prediction about seasonal parasite levels of lambs and ewes. Model inputs were generated by using data from the first 2 years of a 3-year study (2006–2008) which examined the epidemiology of GIN parasitism in Ontario sheep flocks. Required input data included ewe parasite egg output, pasture-related information and management dynamics. Farm visits in 2006 and 2007 provided relevant data that were collected monthly during the grazing season, on six and seven occasions respectively. These data were collected from 10 ewes and 10 lambs on each farm. For 23 Ontario farms with available data, only 11 farms in 2006 and 14 in 2007 had suitable data to run in the model because the Canadian study was not specifically designed with this simulation model in mind. Observed values for faecal egg counts (FEC) were compared to the model FEC outputs and assessed using linear regression analysis. There was adequate fit between observed and simulated data for 8 of the 11 farms modelled using data generated in 2006 ( F = 7.55–42.66, df = 10–11, R 2 = 0.43–0.81, p = 0.021 to