A stochastic model to investigate the effects of control strategies on calves exposed toOstertagia ostertagi

Abstract

SUMMARYPredicting 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.

Modelling the consequences of targeted selective treatment strategies on performance and emergence of anthelmintic resistance amongst grazing calves

“…The current model was based on the simulation approach of Berk et al., 2016a, Berk et al., 2016b, which aims to predict the effects of parasitism with O. ostertagi on a population of growing calves, taking into account host phenotype, host-parasite interactions and parasite epidemiology. The model has been further developed here to account for anthelmintic resistance amongst nematodes, by considering the susceptibility of each nematode genotype to anthelmintic treatment.…”

“…The individual calf model was extended to a stochastic model by considering between-animal variation in calf characteristics (Berk et al., 2016b); between-animal variation was assumed in intrinsic growth rate, body composition (expected protein and lipid content at maturity), maintenance requirements (protein and energy), and immune response traits (rate of acquisition, as well as initial and final rates for the immune traits of establishment, mortality and fecundity). The rates of acquisition in the three immune traits were assumed to follow a log-normal distribution, whereas all other traits were assumed to be normally distributed (Vagenas et al., 2007, Laurenson et al., 2012).…”

“…Additionally the rates of immune acquisition for all 3 immune traits were assumed to be a function of overlapping effector mechanisms (Mihi et al., 2014); thus they were assumed to be strongly correlated (r = +0.5) (Laurenson et al., 2012). Due to the nature of the defined relationships for establishment and mortality it was also necessary to assume a weak correlation (r = −0.2) between minimum mortality and maximum establishment (Berk et al., 2016b). All other traits were assumed to be uncorrelated (Doeschl-Wilson et al., 2008).…”

“…It was assumed that the initial concentration of anthelmintic increased so rapidly in the host tissues that it was possible to ignore the time taken to reach maximum drug efficacy (Toutain et al., 1997, Lifschitz et al., 2000). Previous versions of the model assumed a persistent activity of 3 weeks against O. ostertagi , followed by a decline in efficacy of 0.15 per day for simplicity (Berk et al., 2016b); this was considered a sufficient approximation to the defined curve for the specified treatment.…”

“…Simulation modelling on the other hand may offer an effective alternative, and be highly beneficial in assessing the feasibility of novel control strategies. Here we address these gaps, by developing and using a simulation model that represents calf - Ostertagia ostertagi interactions and the epidemiology of the infection (Berk et al., 2016a, Berk et al., 2016b), in order to test the effectiveness of different TST approaches. O. ostertagi is the parasite of greatest significance in cattle grazing in temperate climates, and as the developed model is stochastic, it allows us to make predictions for the application of TST in a population of calves.…”