Which is the best phenotypic trait for use in a targeted selective treatment strategy for growing lambs in temperate climates?

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

“…Each modelled strategy was compared with the untreated group for its effect on average EBW (providing a similar output to carcass weight) and R allele frequency at the end of the first grazing season (Laurenson et al., 2016). The average weight gain benefit arising from treatment (AWGB, kg) was calculated at the end of the first grazing season when animals were taken off pasture and moved indoors, which was defined as housing ( h ):$$AWG{B}_h=EB{W}_{TS{T}_h}-EB{W}_{C_h}\left(\text{kg}\right)$$where $EB{W}_{TS{T}_h}$ is the EBW at the time of housing ( h ) for a group of calves receiving a given TST strategy and $EB{W}_{C_h}$ is the EBW at time of housing for a group of calves left untreated.…”

Finishing lambs on a chicory-plantain mixture or a temperate grassbased pasture: live weight gain and gastrointestinal parasitism

“…(Rattray, 2003). In a recent paper, Laurenson et al (2016) reported strong correlations (especially after a prepatent period) between worm burden and FEC values across nematode species, supporting the use of the FEC reduction test as a measure of anthelmintic efficacy.…”

Modelling the impacts of pasture contamination and stocking rate for the development of targeted selective treatment strategies for Ostertagia ostertagi infection in calves

“…In reality anthelmintic resistance is influenced by many factors, including: the number of genes and alleles involved (Barnes et al, 1995); the relative impact of resistant and susceptible alleles on efficacy and the persistence of activity; the mode of inheritance (Barnes et al, 1995); the level of pre-existing alleles; and potential reversion to susceptibility via resistant phenotype fitness disadvantages (Leathwick, 2013). Whilst these factors would be expected to alter BPR predictions, if applied equally across all treatment groups the same general principles and patterns would be expected to apply (Laurenson et al, 2016). …”

“…BPR at time of housing was calculated according to Laurenson et al (2016) as follows:${BPR}_h=\frac{{EBW}_{{TST}_h}-{EBW}_{C_h}}{{RAF}_{{TST}_h}-{RAF}_{C_h}}$where ${EBW}_{{TST}_h}$ is the empty body weight (kg) at the time of housing ( h ) for a group of calves receiving a given TST strategy, ${EBW}_{C_h}$ is the empty body weight (kg) at time of housing for a group of calves left untreated, ${RAF}_{{TST}_h}$ is the frequency of the R allele on pasture at time of housing ( h ) for a group of calves receiving a given TST strategy and ${RAF}_{C_h}$ is the frequency of the R allele on pasture at time of housing for a group of calves left untreated.…”

“…However, previous simulation studies have made such comparisons by determining the consequent benefit per R (BPR, kg/R) (Berk et al, 2016c, Laurenson et al, 2016). BPR is calculated as the ratio of the average benefit in weight gain resulting from treatment, relative to the frequency of drug resistance alleles (R) amongst parasites resulting from treatment.…”