A computer model to simulate control of parasitic gastroenteritis in sheep on UK farms |
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| Authors: | Learmount J Taylor M A Smith G Morgan C |
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| Institution: | Central Science Laboratory, Sand Hutton, York YO41 1LZ, United Kingdom. j.learmount@csl.gov.uk |
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| Abstract: | A computer model that simulates the population dynamics and epidemiology of three major species of parasitic nematodes of sheep found in the UK (Telodorsagia Ostertagia] spp., Haemonchus spp. and Trichostrongylus spp.) is described. The model has been developed as a tool for veterinarians and advisors to aid in the implementation of integrated parasite control strategies designed to optimise anthelmintic usage and delay the development of resistance on UK farms. The model represents the parasite life cycle, flock dynamics and the response of individuals with different susceptible and resistant genotypes to the major broad-spectrum classes of anthelmintic available in the UK. Where possible, UK data have been used for the model parameters. The model allows worm control simulations on individual UK farms. Inputs include environmental and farm management variables which impact on the epidemiology of the disease, e.g. regional weather data; flock stocking rates; initial pasture larval contamination levels and species proportions; lambing dates; timing of flock movements to clean pastures; and removal of lambs during the year. Farm management data, as well as nematode egg outputs and grass larval counts, were collected from eight UK farms over a 1-year period for initial validation of the model outputs. The management data for each farm were used as inputs for each model run and model outputs for nematode egg counts from ewes and lambs were compared to the observed data for each farm. Statistical analysis of results shows a positive correlation for observed and simulated counts and regression analysis suggests an acceptable fit between the data. Comparison of observed and simulated outputs for resistance were possible for only one farm due to low numbers of worms developing in the laboratory tests. Additional studies will be necessary before resistance data can be reliably compared. Further validation studies are proposed to ensure that the model is robust and applicable across a diverse range of farm types. The model will be used to demonstrate the advantage, in terms of delaying resistance development, of current guidelines for anthelmintic use and management practices for worm control in sheep. |
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