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Title: A stochastic model to investigate the effects of control strategies on calves exposed to 'Ostertagia ostertagi'
Contributor(s): Berk, Zoe (author); Laurenson, Yan  (author); Forbes, Andrew B (author); Kyriazakis, Ilias (author)
Publication Date: 2016
Open Access: Yes
DOI: 10.1017/s0031182016001438Open Access Link
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Abstract: Predicting the effectiveness of parasite control strategies requires accounting for the responses of individual hosts and the epidemiology of parasite supra- and infra-populations. The first objective was to develop a stochastic model that predicted the parasitological interactions within a group of first season grazing calves challenged by 'Ostertagia ostertagi', by considering phenotypic variation amongst the calves and variation in parasite infra-population. Model behaviour was assessed using variations in parasite supra-population and calf stocking rate. The model showed the initial pasture infection level to have little impact on parasitological output traits, such as worm burdens and FEC, or overall performance of calves, whereas increasing stocking rate had a disproportionately large effect on both parasitological and performance traits. Model predictions were compared with published data taken from experiments on common control strategies, such as reducing stocking rates, the 'dose and move' strategy and strategic treatment with anthelmintic at specific times. Model predictions showed in most cases reasonable agreement with observations, supporting model robustness. The stochastic model developed is flexible, with the potential to predict the consequences of other nematode control strategies, such as targeted selective treatments on groups of grazing calves.
Publication Type: Journal Article
Source of Publication: Parasitology, 143(13), p. 1755-1772
Publisher: Cambridge University Press
Place of Publication: United Kingdom
ISSN: 1469-8161
Fields of Research (FoR) 2008: 070202 Animal Growth and Development
070103 Agricultural Production Systems Simulation
070708 Veterinary Parasitology
Fields of Research (FoR) 2020: 300301 Animal growth and development
300205 Agricultural production systems simulation
300909 Veterinary parasitology
Socio-Economic Objective (SEO) 2008: 970107 Expanding Knowledge in the Agricultural and Veterinary Sciences
Socio-Economic Objective (SEO) 2020: 280101 Expanding knowledge in the agricultural, food and veterinary sciences
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article

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