Towards the targeted control of gastrointestinal parasitism of grazing calves

Abstract

Gastrointestinal parasitism is a ubiquitous challenge to grazing ruminants with negative impacts on animal production. In recent years control of gastrointestinal parasitism has come under threat due to the emergence of anthelmintic resistance. A dynamic, deterministic simulation model was developed to investigate the consequences of parasitism with Ostertagia ostertagi on first season grazing calves. Host-parasite interactions were considered to predict the level of parasitism and performance of an infected calf. Data from published literature were used to parameterise the model, and model sensitivity was tested for uncertain parameters by a Latin hypercube sensitivity design. The model was validated against published literature using graphical and statistical comparisons. Its predictions were quantitatively consistent with the parasitological outputs of published experiments in which calves were subjected to different infection levels. Subsequently, the model was developed into a stochastic one by considering phenotypic variation amongst the calves and variation in parasite supra-population, i.e. parasite populations at all development stages across all hosts. Model behaviour was assessed against variation in parasite supra-population and stocking rate. The model showed the initial pasture infection level to have little impact on parasitological output traits, such as worm burdens and faecal egg counts, or overall performance of calves, whereas increasing stocking rate had a disproportionately large effect on both parasitological output and performance traits. Stochastic model predictions were validated against published data taken from experiments on common control strategies and showed a reasonable agreement with observations in most cases, reinforcing model accuracy. Alternative control strategies that aim to slow anthelmintic resistance by maintaining refugia on pasture, i.e. ensuring a proportion of the parasite population remains unexposed to anthelmintics, were investigated by using the model. In the first instance, this included targeted selective treatments (TST), whereby only individuals that would benefit most from anthelmintic are treated, according to a phenotypic trait criterion. The simulation model compared: 1) the most appropriate phenotypic trait for treatment selection and 2) the method of selection animals for treatment (i.e. treating a fixed percentage of the population versus treating individuals who exceed a given threshold for treatment). Treatment success was assessed in terms of benefit per R (BPR), the ratio of average benefit in weight gain to change in frequency of resistance alleles R (relative to an untreated population). Overall the most beneficial treatment involved treating calves for which their average daily gain fell iii below a threshold level. Subsequently, the effect of different initial pasture contamination levels and stocking rates on the most appropriate phenotypic trait and the most beneficial method of selection for treatment was tested. In general, a greater benefit to treatments was perceived with decreasing initial pasture contamination, with the exception of threshold treatments according to faecal egg counts. Stocking rate had a more variable effect, with the greatest benefit to treatment derived at conventional or high stocking rates, dependent on the determinant criterion and method of selection. It was observed that treating calves when their average daily gain fell below a threshold level was the most beneficial treatment strategy under all investigated scenarios. The work developed here can be used as the basis for the development of TST strategies that minimise the reductions in calf performance whilst simultaneously reducing the rate of development of anthelmintic resistance.