Modelling the consequences of targeted selective treatment strategies
on performance and emergence of anthelmintic resistance amongst
, Yan C.S.M. Laurenson
, Andrew B. Forbes
, Ilias Kyriazakis
School of Agriculture Food and Rural Development, Newcastle University, Newcastle Upon Tyne, NE1 7RU, UK
Animal Science, School of Environmental and Rural Science, University of New England, Armidale, New South Wales, 2351, Australia
Scottish Centre for Production Animal Health and Food Safety, School of Veterinary Medicine, University of Glasgow, G61 1QH, Scotland, UK
Received 3 August 2016
Received in revised form
3 November 2016
Accepted 7 November 2016
Available online 16 November 2016
Targeted selective treatment (TST)
The development of anthelmintic resistance by helminths can be slowed by maintaining refugia on
pasture or in untreated hosts. Targeted selective treatments (TST) may achieve this through the treat-
ment only of individuals that would beneﬁt most from anthelmintic, according to certain criteria.
However TST consequences on cattle are uncertain, mainly due to difﬁculties of comparison between
alternative strategies. We developed a mathematical model to compare: 1) the most ‘beneﬁcial’indicator
for treatment selection and 2) the method of selection of calves exposed to Ostertagia ostertagi, i.e.
treating a ﬁxed percentage of the population with the lowest (or highest) indicator values versus treating
individuals who exceed (or are below) a given indicator threshold. The indicators evaluated were average
daily gain (ADG), faecal egg counts (FEC), plasma pepsinogen, combined FEC and plasma pepsinogen,
versus random selection of individuals. 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). The optimal indicator in terms of BPR for ﬁxed percentages of calves treated was
plasma pepsinogen and the worst ADG; in the latter case treatment was applied to some individuals who
were not in need of treatment. The reverse was found when calves were treated according to threshold
criteria, with ADG being the best target indicator for treatment. This was also the most beneﬁcial strategy
overall, with a signiﬁcantly higher BPR value than any other strategy, but its degree of success depended
on the chosen threshold of the indicator. The study shows strong support for TST, with all strategies
showing improvements on calves treated selectively, compared with whole-herd treatment at 3, 8, 13
weeks post-turnout. The developed model appeared capable of assessing the consequences of other TST
strategies on calf populations.
©2016 The Authors. Published by Elsevier Ltd on behalf of Australian Society for Parasitology. This is an
open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
The control of gastrointestinal parasitism for small ruminants
has long been under threat from the development of anthelmintic
resistance by parasite populations (Kaplan, 2004; Wolstenholme
et al., 2004; Jabbar et al., 2006; Papadopoulos et al., 2012). How-
ever, in recent years it has become evident that this is also an
emerging problem for cattle (Edmonds et al., 2010; Sutherland and
Leathwick, 2011; O'Shaughnessy et al., 2014b; Rose et al., 2015).
With nematode resistance now present to all three of the broad
spectrum anthelmintic classes (benzimidazoles, levamisole and
macrocyclic lactones) used on cattle (Sutherland and Leathwick,
2011), control strategies aiming to sustain effective parasitic con-
trol are of key importance.
Methodologies designed to maintain refugia within nematode
populations can help to reduce the build-up of resistance by pre-
serving susceptible nematode genotypes. A reservoir of susceptible
genotypes on pasture helps to dilute the frequency of resistance
alleles amongst nematodes and maintain anthelmintic efﬁcacy (van
Wyk, 2001; Gaba et al., 2010). One strategy that aims to achieve this
is targeted selective treatment (TST), which involves the treatment
of selected individuals that require, or will beneﬁt from, treatment,
as opposed to treatment of the entire group (van Wyk et al., 2006).
E-mail address: email@example.com (Z. Berk).
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International Journal for Parasitology:
Drugs and Drug Resistance
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2211-3207/©2016 The Authors. Published by Elsevier Ltd on behalf of Australian Society for Parasitology. This is an open access article under the CC BY license (http://
International Journal for Parasitology: Drugs and Drug Resistance 6 (2016) 258e271
Individuals are generally identiﬁed as needing to receive treatment
on the basis of their level of parasitism or performance (Charlier
et al., 2014). Although TST strategies have been developed and
applied successfully in lambs (Greer et al., 2009; Kenyon et al.,
2009, 2013), there are considerably fewer studies on cattle, with
the ﬁrst insights into the application of TST having occurred rela-
tively recently (Greer et al., 2010; McAnulty et al., 2011; H€
et al., 2013; O'Shaughnessy et al., 2014a, 2015a; b). As there are
important differences in host-parasite interactions and parasite
epidemiology between cattle and sheep, differences in the meth-
odology and application of TST in cattle can be expected.
Although TST strategies in sheep have been shown to be bene-
ﬁcial in reducing selection for anthelmintic resistance (Kenyon
et al., 2013), it is difﬁcult to know which of the various strategies
would be most effective under various scenarios. At present there
are no direct comparisons of TST strategies in cattle, in part due to
difﬁculties arising from confounding variables (H€
oglund et al.,
2013; O'Shaughnessy et al., 2015a). Additionally, it is difﬁcult and
time consuming to test such strategies in the long-term. 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 in-
teractions and the epidemiology of the infection (Berk et al., 2016a;
b), 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 pop-
ulation of calves.
2. Materials and methods
The current model was based on the simulation approach of
Berk et al. (2016a; b), 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 ac-
count for anthelmintic resistance amongst nematodes, by consid-
ering the susceptibility of each nematode genotype to anthelmintic
2.1. Host-parasite interactions
Brieﬂy, it was assumed that a healthy calf attempts to ingest
sufﬁcient nutrient resources to meet demands for growth and
maintenance (Coop and Kyriazakis, 1999). In the presence of
parasitism, resource requirements increase due to endogenous
protein losses to the calf (Fox, 1993). It is further assumed that the
calf acquires immunity to reduce the impact of infection
(Claerebout and Vercruysse, 2000), and by doing so further in-
creases resource (e.g. protein) requirements. In addition to the
endogenous protein loss and the increased resource requirements,
a reduction in appetite and feed intake accompanies infection (Fox
et al., 1989; Forbes et al., 2000; Kyriazakis, 2014). Although com-
plex, the mechanism for inappetance in ostertagiosis was modelled
as a function of the rate of immune acquisition, as it has been
suggested that this reduction is associated with components of the
immune response (e.g. cytokines), and related pathological and
inﬂammatory responses (Fox et al., 1989; Kyriazakis, 2010, 2014).
Consequently, the calf consumes insufﬁcient resources to fulﬁl its
requirements. Ingested protein is usually the ﬁrst limiting nutrient
resource. Once the protein loss due to parasitism has been
accounted for it was assumed that allocation of limited resources
were prioritised towards maintenance and repair (Coop and
Kyriazakis, 1999). Remaining resources were then allocated
between growth and immunity, proportional to their requirements
(Kahn et al., 2000; Doeschl-Wilson et al., 2008; Laurenson et al.,
2011). The model was parameterised such that the calf and its
growth represented a weaned, castrated male (steer) Limousin x
Holstein Friesian born in autumn (Berk et al., 2016a).
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 ¼þ0.5) (Laurenson et al.,
2012). Due to the nature of the deﬁned relationships for estab-
lishment and mortality it was also necessary to assume a weak
correlation (r ¼0.2) between minimum mortality and maximum
establishment (Berk et al., 2016b). All other traits were assumed to
be uncorrelated (Doeschl-Wilson et al., 2008). Further, random
variation in feed intake was included to achieve a phenotypic cor-
relation between food intake and growth rate of approximately 0.8
(Cammack et al., 2005).
2.2. Epidemiological module
In the epidemiological module of Berk et al. (2016b), the grazing
pasture was deﬁned by the number of hectares and pasture avail-
able for grazing (Sibbald et al., 2000), taking into account grass
growth and grass consumption on a daily basis. Pasture was
assumed to be initially contaminated with overwintered eggs and
larvae; subsequent larval contamination of pasture was assumed to
arise from eggs excreted by infected calves. The development
period from eggs to larvae and the larval mortality were assumed to
be temperature-dependent (Stromberg, 1997); the resultant larvae
on pasture were considered to have an aggregated distribution.
Calves were assumed to graze randomly across the pasture
(Laurenson et al., 2011) and consume larvae, removing them from
pasture, thus completing the parasitic lifecycle.
2.3. Parasite anthelmintic resistance
The mechanism for the development of anthelmintic resistance
by O. ostertagi to a wide spectrum of anthelmintics is currently not
well understood; however there is growing evidence to support a
polygenic mechanism (Wolstenholme et al., 2004; Gilleard and
Beech, 2007; Prichard, 2007; Yazwinski et al., 2009; Kotze et al.,
2014). In the ﬁrst instance resistance to a single anthelmintic
drug, ivermectin, was assumed to be controlled by two genes, each
consisting of two alleles. Subsequently, nine possible allele com-
binations were identiﬁed (Barnes et al., 1995). Each allele was
assumed to have equal expression within the phenotype (i.e. per-
fect gene and allele neutrality) hence conveying the same degree of
either resistance (R) or susceptibility (S) (Barnes and Dobson,1990).
Ivermectin action was segregated into four key components; a) the
degree of dominance of the resistance allele (R), b) drug efﬁcacy
against each nematode genotype, c) drug efﬁcacy against each
parasitic developmental phase and d) the persistence activity of the
drug, which was assumed to be a pharmacokinetic trait of the drug
and thus independent of resistance (Smith et al., 1999).
The nine possible genotypes constitute 4 different phenotypic
Z. Berk et al. / International Journal for Parasitology: Drugs and Drug Resistance 6 (2016) 258e271 259
expressions; these were assumed to show a graded response from
) to resistant (R
)(Barnes et al., 1995),
dependent on the number of R alleles present as represented in
Fig. 1. For example, the genotype combination S
considered to have the same phenotype as S
. Additionally it
has been observed that the efﬁcacy of ivermectin is not the same
across all stages of development (Eddi et al., 1997; Vercruysse et al.,
2000; Yazwinski et al., 2009), hence the efﬁcacy for each stage was
deﬁned according to Yazwinski et al. (2009).
Ivermectin is known to display persistent activity of between 1
and 4 weeks against gastrointestinal nematodes in cattle when
administered subcutaneously at a rate of 200
(Armour et al., 1985; Borgsteede and Hendriks, 1986; Williams and
Broussard, 1995; Ranjan et al., 1997). This variation in the length of
persistent activity can be explained by innate differences in sensi-
tivity amongst various nematode species, environmental factors,
such as level of infection (Vercruysse et al., 2000) and within and
between differences in pharmacokinetics amongst cattle breeds
(Toutain et al., 1997). A curve describing the decay of ivermectin
efﬁcacy as a declining sigmoidal function of time was adapted from
the equation used by Smith et al. (1999) (equation (1)). The efﬁcacy
of a given genotype x(Efficacy
) at time twas deﬁned, whereby
efﬁcacy falls between 0 and 1, 0 signifying the drug to have no effect
and 1 signifying complete effectiveness.
where tis time, w
are constants and w
is a parameter that
depends on parasite genotype (see below).
Parameters were ﬁtted to published literature to show the ex-
pected persistence activity of ivermectin against O. ostertagi para-
sites (Armour et al.,1985; Borgsteede and Hendriks,1986; Williams
and Broussard, 1995; Toutain et al., 1997; Ranjan et al., 1997); as
¼0.47 and w
was dependent on the drug efﬁcacy
which was deﬁned separately for each genotype according to the
number of R alleles present. Drug efﬁcacy against the susceptible
genotype was deﬁned according to Yazwinski et al. (2009); how-
ever, estimates do not exist for the resistant genotypes. It was
therefore necessary to make assumptions about this; it was
assumed that drug efﬁcacy against the completely resistant
genotype (RRRR) was 0.01 with each R allele assumed to contribute
equally to reduction in efﬁcacy (Leathwick et al., 1995; Laurenson
et al., 2013). As an example, drug activity against adult worm ge-
notypes is demonstrated in Fig. 1. It was assumed that the initial
concentration of anthelmintic increased so rapidly in the host tis-
sues 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
The resistance genotypes of the initial nematode population on
pasture were assumed to arise from random mating, assuming
Hardy-Weinberg equilibrium, from an initial frequency of the
resistance (allele) assumed to be 0.001 (Barnes and Dobson, 1990).
Subsequently, the frequency of R in the worm burden (WB) of each
host was used to calculate the frequencies of each genotype in the
excreted eggs, again assuming Hardy-Weinberg equilibria. Once the
new eggs had hatched and developed into larvae their contribution
to the genetic makeup of larvae on pasture was accounted for. It
was assumed that all genotypes were equally ﬁt on pasture, such
that in the absence of anthelmintic drenching the frequency of R
remains the same throughout the simulated grazing season. The
total frequency of each genotype in hosts and on pasture was
tracked on a daily basis, along with the frequency of R.
2.4. Treatment strategies
2.4.1. Timing of treatments
The most appropriate timings for dosing with the antiparasitic
drug were determined by simulating a population of untreated
calves to predict nematode population (adult worms), pasture
contamination (PC) (L
/kg DM) and bodyweight gain (kg). It was
observed that at approximately 8 weeks post-turnout both para-
sitic burden and PC began to increase and bodyweight gains were
compromised; this coincides with experimental ﬁndings in which
the majority of calves beneﬁted from treatment at 8 weeks
oglund et al., 2013; O'Shaughnessy et al., 2015b). In line with
O'Shaughnessy et al. (2015a) the simulations support a second
treatment at approximately 16 weeks. An 8-week interval between
ivermectin treatments in cattle is based on ~4 weeks of persistent
activity against common gastrointestinal nematodes (NOAH, 2015),
an average pre-patent period of three weeks and a week of limited
exposure to infection (Shaw et al., 1998b). There are no recent
studies into the changes in persistence activity due to the build-up
2.4.2. Key quantiﬁable host features
Key quantiﬁable traits that can be observed non-invasively to
provide an indication of the parasitic load (or resulting compro-
mised performance) were identiﬁed. Performance can easily be
quantiﬁed by average daily bodyweight gain (ADG) (kg/d). This was
preferable to bodyweight (kg) as variation in initial bodyweights is
accounted for; hence any reduction can be attributed to parasitism
oglund et al., 2009). Direct measures of parasitic load are more
complex; the most appropriate and widely used measures were
concluded to be faecal egg counts (FEC) (eggs/g) and plasma
pepsinogen (international units of tyrosine/litre (IUT/l)), both
having their own limitations. Elevated pepsinogen levels occur
from around 2e3 weeks as young adult worms emerge from the
gastric glands (Jennings et al., 1966; Ritchie et al., 1966). All these
traits have shown promising outcomes for the success of TST in
practice (Greer et al., 2010; McAnulty et al., 2011; H€
oglund et al.,
2013; O'Shaughnessy et al., 2014a, 2015a; b), therefore
Fig. 1. The assumed efﬁcacy, i.e. the mortality success of the drug, over time for which
a single treatment with ivermectin is effective against adult Ostertagia ostertagi. The
efﬁcacy is shown for corresponding worm genotypes with zero, one, two, three and
four alleles for resistance; each R allele is assumed to decrease drug efﬁcacy by equal
Z. Berk et al. / International Journal for Parasitology: Drugs and Drug Resistance 6 (2016) 258e271260
relationships for these traits had to be deﬁned within the model.
Pepsinogen concentrations are considered to be a good diag-
nostic tool for abomasal damage associated with O. ostertagi bur-
dens in cattle for the duration of the ﬁrst grazing season (Charlier
et al., 2014); a strong correlation has been observed between
adult worm numbers and pepsinogen levels (Anderson et al., 1966;
Allen et al., 1970; Baker and Gershwin, 1993; Dorny et al., 1999).
Concurrent measurements of WB and pepsinogen were obtained
from existing literature (Anderson et al., 1966; Snider et al., 1981;
Williams et al., 1987; Baker and Gershwin, 1993; Almería et al.,
1996; Szyszka and Kyriazakis, 2013). In the case of Szyszka and
Kyriazakis (2013) only pepsinogen was recorded, however as the
infections were artiﬁcially administered it was possible to replicate
the experimental conditions within the model and hence simulate
predicted WB associated with elevated pepsinogen levels. The
model only considers sub-clinical infections, hence pepsinogen
levels above 5 IUT/l were ignored, as these are considered to be
clinical (Hilderson et al., 1989; Shaw et al., 1997; Vercruysse and
Claerebout, 2001). Pepsinogen levels would be expected to in-
crease as adult worms emerge from gastric glands, causing elevated
abomasal pH and leakage due to increased mucosal permeability
(Jennings et al., 1966; Allen et al., 1970; Fox et al., 1987); they will
continue to increase with increasing WB until a plateau is achieved
as no further changes in gastric function occur (Dorny et al., 1999).
Consequently, a monomolecular growth function was ﬁtted to the
published data for concurrent WB and pepsinogen levels; this
equation provided the best ﬁt and mirrored the expected rela-
tionship between WB and pepsinogen:
is the maximum pepsinogen for a sub-clinical
infection (3.8 IUT/l), Pep
is the minimum pepsinogen, observed
in a healthy calf (0.8 IUT/l) and C
is a rate constant deﬁning the
relationship between WB and pepsinogen level (1.67 10
(R ¼0.603, RMSE ¼0.636). Pepsinogen levels do not provide an
exact description of the WB, for this reason random variation in
pepsinogen was added and parameterised to mirror a correlation
between WB and pepsinogen of approximately 0.7 (Anderson et al.,
1966; Allen et al., 1970; Baker and Gershwin, 1993; Dorny et al.,
2.4.3. Targeted selective treatment strategies
The aim of this study was to compare the consequences of
control strategies and identify the most effective and sustainable
method(s). To provide a baseline for comparison, treatment groups
included calves administered no treatment and strategically
treated calves with the whole group receiving anthelmintic dosing
at the time points of 3, 8 and 13 weeks post-turnout; this has been
shown to provide good control of parasitic gastroenteritis in set-
stocked, ﬁrst grazing season calves (Shaw et al., 1998a). Subse-
quently, a variety of TST strategies were simulated (detailed below)
using the aforementioned traits of ADG, FEC and pepsinogen as
determinant criteria for treatment. A summary of the different TST
strategies investigated is provided in Table 1.
220.127.116.11. TST based on herd percentages. One speciﬁcation for TST is
to dose a ﬁxed percentage of calves selected according to a pre-
determined criterion (Laurenson et al., 2013). In order to investi-
gate a range of scenarios, treatments were assumed to occur for 10,
25, 50 and 100% of the host population, as indicated by each of the
determinant criteria; 100% signifying whole group targeted treat-
ment. Calves within a population were treated at the speciﬁed
times, subject to a determinant criterion: for ADG the calves with
the lowest gains were preferentially treated; for FEC and pepsin-
ogen the calves with the highest values were preferentially treated.
A total of 2 days was allowed for processing and analysis of the
samples; ivermectin was then assumed to be administered the
following day at 200
g/kg bodyweight (H€
oglund et al., 2013;
O'Shaughnessy et al., 2014a). An additional comparison group
was included whereby calves were selected for treatment at
random by generating random pseudo-numbers relating to calf ID
numbers; as such, the other determinant criteria were evaluated in
relation to this.
18.104.22.168. TST based on threshold values. In contrast to selecting a
ﬁxed percentage of the herd for treatment, TSTcan also be achieved
by dosing calves when a determinant criterion reaches a threshold
level (Charlier et al., 2014). The same 3 determinant criteria were
investigated, with the addition of a group of calves treated ac-
cording to a combination of FEC and pepsinogen, as this strategy
has been investigated in the ﬁeld (O'Shaughnessy et al., 2014a,
2015a; b). Available literature was used to deﬁne threshold values
for each determinant criterion. When using ADG as the determi-
nant criterion, calves were treated when individual ADG was
inferior to the ADG averaged over the poorest growing 50% of calves
in a strategically treated group (3, 8 and 13 weeks) (H€
oglund et al.,
2013). The threshold for FECs was considered to be 80 eggs/g. A
trigger of 200 eggs/g has been used previously, however this was
deﬁned for mixed infections (O'Shaughnessy et al., 2014a).
Although seasonal variation in egg ratios is observed in temperate
regions (Dorny et al.,1988; Vercruysse et al., 1988; Verschave et al.,
2014), for simplicity it was assumed that an average proportion of
0.4 was O. ostertagi eggs (Dorny et al., 1988; Vercruysse et al., 1988;
Hilderson et al., 1990; Ploeger and Kloosterman, 1993; Almería
et al., 1996; Areskog et al., 2013; Verschave et al., 2015). The
threshold for pepsinogen levels was assumed to be 2 IUT/l and
therefore the ﬁnal group involved treating calves when both FECs
greater than 80 eggs/g and pepsinogen levels greater than 2 IUT/l
were attained by an individual. For all determinant criteria, trait
measurements were assumed to be taken every 3 weeks starting
from 8 weeks post-turnout (Greer et al., 2010; H€
oglund et al., 2013;
O'Shaughnessy et al., 2014a, 2015a; b) and treatment applied to
individuals presenting measurements above or below the speciﬁed
threshold. The reduction in anthelmintic use was calculated as a
percentage of the total anthelmintic applications administered in
the strategically treated group.
2.5. Simulation procedure and outputs
A population of 500 calves was simulated on pasture over their
ﬁrst grazing season for a period of 6 months from weaning. All
calves were assumed to be parasitologically naïve prior to turn-out
to pasture at a conventional stocking rate of 5 calves/Ha (AHDB,
2013) and an initial PC of 200 L3/kg DM (Larsson et al., 2007).
The same population was modelled for all treatment groups. All
model simulations were programmed in MATLAB (2015b).
A population of calves was simulated for each of the selected
strategies. Outputs were recorded on a daily basis and compared for
the following: performance traits (population average of empty
body weight (EBW, kg)), parasitological traits (population average
of WB and FEC), epidemiological traits (PC (L
/kg DM grass)) and
anthelmintic resistance traits, such as the frequency of R in the
nematode population on pasture and total number of anthelmintics
administered over the grazing season.
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
Z. Berk et al. / International Journal for Parasitology: Drugs and Drug Resistance 6 (2016) 258e271 261
(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):
is the EBW at the time of housing (h) for a group of
calves receiving a given TST strategy and EBW
is the EBW at time
of housing for a group of calves left untreated.
Similarly, for each treatment strategy the frequency of R allele
was compared with the untreated control group to determine the
impact upon anthelmintic resistance. The increase in R allele fre-
) from turnout to the end of the grazing season was
calculated at housing:
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
is the frequency of the R allele on pasture at time of housing
for a group of calves left untreated.
In order to evaluate each of the simulated strategies, the ‘beneﬁt
per R’(BPR) was calculated to account for production beneﬁts and
the impact on anthelmintic resistance such that equal weighting
was given to both traits. BPR at time of housing was calculated
according to Laurenson et al. (2016) as follows:
As such, the best strategy will be the one displaying the highest
value for BRP.
To make a comparison of the beneﬁt gained from treating a
percentage of calves according to each determinant criteria relative
to random selection, a number of outputs were assessed in terms of
their ﬁnal predicted values at the end of the grazing season (day
180); these were: A) cumulative faecal egg counts as a measure of
parasitism; B) relative reductions in EBW gain as a measure of
performance; C) frequency of R on pasture as a measure of resis-
tance and D) BPR value. A two-tailed Z test was carried out to assess
the statistical signiﬁcance of treatments according to each deter-
minant criterion, with the exception of relative reductions in EBW
gain which were assessed using the Mann-Whitney Utest due to
the skewed data distribution. For outputs related to resistance
(frequency of R on pasture and BPR) the output was a single mea-
sure for the complete pasture and therefore variation was esti-
mated by simulating 10 populations for each treatment group. In
each simulation, all stochastic parameters describing individuals
and their environment were assigned based on a different unique
sequence of computer-generated random numbers. The statistical
tests revealed whether treatments according to determinant
criteria produced outputs different from what might be obtained by
random selection. All statistical comparisons were carried out to
the 95% conﬁdence level. Additionally, the model recorded which
individuals were treated at each assessment, from this the number
of treatments shared between groups treated according to different
determinant criteria was calculated along with the number of
repeat treatments made within each treatment group, i.e. per-
centage of the individuals receiving treatment at the ﬁrst assess-
ment to also receive treatment at the second assessment. A
comparison of traits used for the threshold treatments was made
for BPR using the same methods, there was no standard control to
compare all treatments to and therefore they were compared with
3.1. TST based on herd percentages
3.1.1. Comparison of treatment percentages
The impact of different percentages of treated calves was
investigated for determinant criteria of ADG, FEC and pepsinogen.
The pattern of outcomes for different percentages of the population
treated was similar for all determinant criteria and for this reason
the outputs for the determinant criterion ADG are shown on Fig. 2.
The impact of treatments on the parasitological output of average
WB (Fig. 2A) over one grazing season showed a reduction in peak
WB, remaining below that of the untreated group throughout the
grazing season. The larger the percentage of calves treated the
lower the average WB. This patternwas reﬂected in the average FEC
(Fig. 2B); average FEC was reduced from the ﬁrst anthelmintic
treatment on 56 day post-turnout (dpt) until approximately
105 dpt, when all groups showed an increase in FEC to values equal
to or greater than those of an untreated group of calves. The effects
were more pronounced when a greater percentage of calves were
treated. Following the second anthelmintic treatment, FECs were
again reduced relative to the percentage treated; at approximately
155 dpt all treated groups showed an increase to levels above the
untreated group. The observed increase was larger when a greater
percentage of calves were treated, with the 100% treated group
showing the largest ﬁnal FEC.
Pasture contamination (PC) expressed as L3/kg grass DM
(Fig. 2C) was reduced by the treatments relative to the untreated
herd, the extent of the reduction was higher the greater the per-
centage of calves treated. For the group treated at 100%, PC
continued to rise for 2e3 weeks following the ﬁrst treatment due to
developing eggs already present on pasture pre-treatment. A sub-
sequent trough in PC was observed. The ﬁnal PC was approximately
the same for all treated and untreated groups. As a result of lower
WB and PC prompted by anthelmintic treatments the impacts of
parasitism on the relative reduction in EBWgain (compared with a
healthy control population) was less for the groups with the highest
percentage of calves treated for any of the determinant criteria
Predictably, the treatments most successful at reducing parasi-
tological burdens and reductions in weight gain were also most
likely to result in a high frequency of resistant (R) alleles in the
nematode population at pasture. Fig. 2E shows the change in fre-
quency of R allele on pasture; as would be expected the larger the
percentage of treated calves the greater the increase in R allele
frequency, with disproportionally large increases observed when
the percentage treated was increased. For example, the increase in
frequency of R was 0.0007 and 0.0043 when 50 and 100% of the
population were treated. In all cases the frequency of R increased
following each anthelmintic treatment. Increasing the percentage
A summary of the different control targeted selective treatment (TST) strategies
investigated for differing methods of selection for treatment; ADG ¼Average Daily
Gain (kg/d); FEC¼Faecal Egg Counts (eggs/g).
Treating a ﬁxed percentage of the
population with the lowest
(or highest) trait values
Treating individuals who
exceed (or are below)
a given trait threshold
Z. Berk et al. / International Journal for Parasitology: Drugs and Drug Resistance 6 (2016) 258e271262
of the population treated increased the impact upon the R allele
frequency. As such, the pattern predicted for the largest treatment
percentage of 100% (whole-herd treatment) was the most exag-
gerated as a consequence of a reduction in S alleles in eggs
deposited onto pasture and a reduction in PC. Following this initial
increase, the R allele frequency continued to vary as a consequence
of the impact of treatment upon PC coupled with the continued
persistent activity of ivermectin. This effect was most notable as a
secondary peak in R allele frequency on pasture, prior to the impact
of the second anthelmintic, for the whole-herd treatment group.
This secondary peak in R allele frequency decreased around 115 dpt
reﬂecting the increase in PC as the persistent effect of ivermectin
3.1.2. Comparison between determinant criteria
Fig. 3 provides a comparison of population averages for cumu-
lative FEC, ﬁnal relative reduction in EBW (in comparison to
uninfected controls), ﬁnal frequency of R on pasture and BPR value
for groups of calves drenched at different percentages according to
the different determinant criterion traits of ADG, FEC, pepsinogen
or random selection. The optimal determinant criterion would be
the one that offers a small change in the frequency of R whilst
preventing extreme reductions in EBW gains. A statistical com-
parison of the beneﬁts to cumulative FEC, reduction in ﬁnal EBW
gain, ﬁnal frequency of R on pasture and BPR of treating according
to each determinant criterion was made in relation to treating ac-
cording to random selection.
Fig. 3A shows the population average and standard error of
cumulative FEC, which was used as an indicator of parasitism.
Treating calves according to pepsinogen levels showed similar ef-
fects to random selection, whereas treatment according to the
determinant criteria of FEC or ADG was more effective at reducing
FEC, with ADG being predicted to have the greatest improvement
over random selection, signiﬁcant for groups where 25% and 50% of
Fig. 2. Predictions for groups of calves either left untreated or treated at weeks 8 and 16 according to lowest average daily bodyweight gain (ADG, kg/d) when a percentage of 0,10,
25, 50 and 100% of a herd of 500 calves grazing on pasture initially contaminated with 200L
/kg DM grass were treated with ivermectin; the population averages are presented for
outputs of A) worm burden; B) faecal egg output (FEC) (eggs/g); C) pasture contamination (L
/kg DM grass); D) relative reduction in empty bodyweight gain relative to a non-
parasitised population (kg) and E) the frequency of resistant parasite genotype R on pasture.
Z. Berk et al. / International Journal for Parasitology: Drugs and Drug Resistance 6 (2016) 258e271 263
calves treated. The differences between determinant criteria
increased with increasing percentages of treated calves, with the
FEC treated group also showing signiﬁcant improvements over the
random selection group when 25% and 50% of the population was
Fig. 3B shows the consequences of parasitism on performance;
all groups showed similar reductions in ﬁnal EBW gain. Groups
treated according to FEC yielded marginally greater improvements
in EBW gain (i.e. smallest relative reduction in EBW gain in com-
parison to a non-parasitised group), with the difference being sig-
niﬁcant when 25% of the population was treated. In contrast,
groups treated according to ADG showed the least improvement
(i.e. largest relative reduction in EBW gain in comparison to a non-
parasitised group), whilst being accompanied by the largest range
of values within the population. In contrast to cumulative FEC
outcomes, the ﬁnal frequency of R shown in Fig. 3C was highest for
groups treated according to FEC and ADG with a signiﬁcant increase
observed relative to calves treated according to random selection
for all treatment percentages, whereas there was no signiﬁcant
difference between calves treated according pepsinogen and
random selection. Again, this effect was clearer for greater per-
centages of treated calves. This was conveyed in the BPR values
(Fig. 3D): calves treated according to ADG and FEC showed a
signiﬁcantly lower value than predicted for random selection,
whereas when treated according to pepsinogen there was no sta-
tistical difference. The largest differences between determinant
criteria were observed when a smaller percentage of calves were
treated, along with the largest variation between populations.
When 100% of the herd was treated there was no difference be-
tween determinant criteria and therefore it was not possible to
conduct a statistical comparison, however it should be noted the
average BPR value was 4012 (181) which is notably lower than the
value observed for any of the other treatment percentages
Treatment strategies were further compared by examining the
individuals selected at each treatment stage. Table 2 gives the
percentage of total treatments that were shared between pop-
ulations treated according to different determinant criteria. As can
be seen, treatment according to ADG or FEC shared more individual
treatments than would be expected by random probability whereas
ADG and pepsinogen shared fewer. It was also possible to examine
whether individuals treated on the ﬁrst occasion are more or less
likely to be selected on the second occasion; this statistic is also
shown in Table 2. Both ADG and FEC showed a greater number of
repeat treatments than would be expected at random with ADG
showing the largest number of repeat treatments. Conversely,
groups treated according to pepsinogen showed fewer repeat
treatments than would be expected at random.
Fig. 3. End of season (day 180) predictions for: A) cumulative faecal egg count (eggs/g), B) relative reduction in empty bodyweight gains (kg) in comparison to a non-parasitised
population, C) frequency of R on pasture, and D) beneﬁt per R (BPR) representing the beneﬁt in empty bodyweight gain (kg) per change in frequency of R; for 500 calves grazing on
pasture initially contaminated with 200L
/kg DM grass. Anthelmintic treatment was administered at weeks 8 and 16 to either 10, 25 or 50% of the population according to lowest
average daily bodyweight gain (ADG, kg/d), highest faecal egg count (FEC, eggs/g), highest plasma pepsinogen (IUT/I) or selected at random. Predictions for frequency of R on
pasture and beneﬁt per R (BPR) are provided as an average of ten simulations. Statistical indications are provided for each treatment group in comparison to those selected for
treatment at random.
Z. Berk et al. / International Journal for Parasitology: Drugs and Drug Resistance 6 (2016) 258e271264
3.2. TST based on threshold values
The impact of deﬁning a threshold level for treatment for the
different determinant criteria of ADG, FEC, pepsinogen and the
combination of FEC and pepsinogen was assessed in terms of the
parasitological outputs of WB (Fig. 4A) and FEC (Fig. 4B). Following
the ﬁrst assessment for treatment, all groups showed a lower peak
in WB and FEC than that of an untreated group of calves, although
the reductions observed were minimal in the group treated ac-
cording to a combination of FEC and pepsinogen. The largest re-
ductions in WB, and consequently FEC, were observed when the
determinant criterion was pepsinogen; this was then followed by
groups where the determinant criterion was ADG and ﬁnally FEC.
Reductions in WB and FEC started earlier when ADG and FEC were
used as determinant criteria, compared with the other groups with
notable sudden decreases in WB for the pepsinogen group from
98 dpt. For the remaining determinant criteria the decline in WB
and FEC was smoother across the grazing period. The strategically
treated group in which the whole-herd treatments were applied at
3, 8 and 13 weeks post-turnout showed very low burdens for the
duration of the season, with a clear increase observed at the end of
the season (from 130 dpt).
As per parasitological traits there was a reduction in peak PC
relative to an untreated control for all treatment groups (Fig. 4C);
again the decrease predicted for combined FEC and pepsinogen
showed minimal reductions. The PC predictions for determinant
criteria largely mirrored the predictions in WB and FEC with the
reduction occurring more rapidly when pepsinogenwas used as the
determinant criterion. All treatment groups showed an improve-
ment upon the untreated group for relative reduction in body
weight gain in comparison to a non-parasitised population
(Fig. 4D). Consistent with reduced parasitological burdens and PC,
the groups treated strategically showed EBW close to that expected
of a healthy (non-parasitised) calf. The groups treated according to
pepsinogen and ADG showed the least reductions in EBW relative
to a healthy (non-parasitised) population of calves, followed by FEC,
and then the combination of FEC and pepsinogen which showed
minimal improvements compared with an untreated groups of
However, upon comparing the frequency of R in the group
administered strategic treatment (whole-herd treated at 3, 8 and 13
weeks post-turnout) an increase in the frequency of R (Fig. 4E)
compared with all other strategies was evident, with large in-
creases observed up until approximately 135 dpt, coinciding with
the increase in eggs excreted to pasture. For this reason outputs for
this treatment are shown separately. Fig. 4F shows the frequency of
R for the different TST groups. The group treated according to the
determinant criterion of pepsinogen alone was seen to give the
largest increase in R, followed by ADG and FEC treated groups both
of which showed an increase in frequency less than half that of the
pepsinogen group. In agreement with other outputs, the group
treated according to both FEC and pepsinogen showed minimal
changes in the frequency of R.
Fig. 5 represents the BPR values for each of the strategies; the
highest value and therefore most beneﬁcial was attributed to the
group treated according to ADG. FEC was the next best strategy,
closely followed by those treated according a combination of FEC
and pepsinogen, then pepsinogen alone. Strategically treated
groups were predicted to have a dramatically lower BPR value. The
difference between each treatment group was observed to be
substantial in all cases. Additionally, the reductions in anthelmintic
applications for each strategy compared with strategic treatment
were calculated and revealed that the combination of FEC and
pepsinogen showed reductions of 98.3%, closely followed by
treatment according to FEC for which a 93.4% reduction was
observed. Considerably more treatments were applied for ADG and
pepsinogen treated groups with reductions of 47.0% and 68.4%
With the emergence of anthelmintic resistance in GI parasites of
cattle (Edmonds et al., 2010; Sutherland and Leathwick, 2011;
O'Shaughnessy et al., 2014b; Rose et al., 2015) there have been at-
tempts towards developing TST strategies for cattle. This is impor-
tant, as although resistance has been slow to develop amongst
cattle parasites, it appears that multi-drug resistance for multiple
parasite species is developing more rapidly than expected
(Sutherland and Leathwick, 2011). There are a number of challenges
to address when developing and assessing such strategies. The ﬁrst
is the basis upon which these strategies are developed. Secondly, it
is difﬁcult to make direct comparisons on the effectiveness of such
strategies through ﬁeld studies due to confounding variables, such
as climatic conditions or management techniques (O'Shaughnessy
et al., 2015a). These will have consequences on the underlying
infection levels and subsequently affect the perceived success of
any treatment strategy. It is therefore unclear from the literature as
to which strategy might be most beneﬁcial in treating the effects of
parasitism whilst delaying the development of resistance. Finally, in
practice it is difﬁcult to assess the development of resistance,
especially over a short time-scale (Besier, 2012; Sutherland and
Bullen, 2014), which is usually the case with experimentation.
A comparison of TST strategies whereby 10, 25 and 50% of calves were treated at 8 and 16 weeks either at random or according to lowest average daily bodyweight gain (ADG,
kg/d), highest faecal egg count (FEC, eggs/g) or highest plasma pepsinogen (IUT/I). Values provided represent the percentage reduction in anthelmintic use relative to a
population of calves treated strategically at 3, 8 and 13 weeks post-turnout. Additionally, the number of treatments shared between groups treated according to ADG, FEC or
pepsinogen are provided. Within each treatment group a record was made of the number of individuals that had been treated at the ﬁrst assessment that were also treated at
the second assessment. The expectation of each occurring at random is provided as a comparison.
Determinant criteria Percentage of herd treated
10% 25% 50%
% reduction in anthelmintic use
e93% 83% 67%
% of shared treatments between determinant criteria Random 10.0% 25.0% 50.0%
ADG-FEC 20.0% 32.0% 55.6%
ADG -Pepsinogen 4.0% 16.4% 42.2%
FEC-Pepsinogen 7.0% 27.6% 48.6%
%ofﬁrst treated group to be selected for second dose Random 10.0% 25.0% 50.0%
ADG 84.0% 87.2% 90.0%
FEC 26.0% 39.2% 70.0%
Pepsinogen 2.0% 18.4% 40.4%
Comparative to strategically treated calves (3, 8 and 13 weeks).
Z. Berk et al. / International Journal for Parasitology: Drugs and Drug Resistance 6 (2016) 258e271 265
Currently faecal egg count reduction tests (FECRT) are used to
assess this, however this technique has only been validated for
sheep and not cattle nematodes (Sutherland and Bullen, 2014).
Compared with sheep nematodes, O. ostertagi tends to show less
aggregation between hosts, excrete fewer eggs (Demeler et al.,
2010; El-abdellati et al., 2010; Yazwinski et al., 2013) and FEC are
generally less reﬂective of WB as a result of density-dependent
effects on parasite fecundity (Michel et al., 1978; Smith et al.,
1987). As a result, the limited numbers of studies conducted on
cattle TST have focused on performance and total number of
anthelmintic applications. In this paper, the relative success of
different TST applied here was evaluated on the basis of BPR, the
ratio of average beneﬁt in weight gain to change in frequency of R
(relative to an untreated population).
With these difﬁculties in mind we embarked upon further
developing a recently published population model to predict the
consequences of different TST strategies on cattle and their
O. ostertagi populations (Berk et al., 2016b). We were particularly
interested in the consequences of: 1) the most appropriate deter-
minant criteria for treatment selection and 2) the method of
selecting animals for treatment, the contrast being treating a ﬁxed
percentage of the population with the lowest (or highest) trait
values versus treating individuals who exceed (or are below) a
given trait threshold for treatment. As the model was population-
based, it allowed us to trace individual animals within a group
and select individuals on the basis of the different methods. The
model was applied to ﬁrst season grazing calves infected with
O. ostertagi, the most important parasite affecting health and pro-
ductivity in temperate climates. Strategies were selected on the
basis of literature; however different methods of deﬁning threshold
triggers have been proposed, in particular for ADG. H€
oglund et al.
(2009) suggested that an ADG below 0.75 kg/d would provide a
good trigger threshold for treatment; however a set value does not
account for the sigmoidal nature of growth or indeed for variability
in intrinsic growth between and within genotypes. For example,
healthy calves that are close to their maximal weights and hence
show slower growth would be considered to require treatment.
However, the risk of this misinterpretation may not be a major
concern for the time interval considers, as calves were probably in
the linear growth phase. Greer et al. (2010) and McAnulty et al.
(2011) proposed determining the expected ADG for individuals at
any given time point dependent on individual calf bodyweight
Fig. 4. Predictions for groups of calves either left untreated, strategically treated with ivermectin at 3, 8 and 13 weeks post-turnout, or treated with ivermectin according to
threshold values for different determinant criteria of average daily bodyweight gain (ADG, kg/d), faecal egg count (FEC, eggs/g), plasma pepsinogen (IUT/l) or the combination of
values for FEC and plasma pepsinogen; were made for a herd of 500 calves grazing on pasture initially contaminated with 200L
/kg DM grass. The population averages are presented
for outputs of A) worm burden; B) FEC (eggs/g); C) pasture contamination (L
/kg DM grass); D) relative reduction in empty bodyweight gain relative to a non-parasitised population
(kg); E) the frequency of R on pasture for the strategically treated group and F) the frequency of R on pasture for the remaining strategies.
Z. Berk et al. / International Journal for Parasitology: Drugs and Drug Resistance 6 (2016) 258e271266
measured at the previous time point. Although a signiﬁcant
improvement to the previous method, there are also problems
associated with this, which arise from the natural uncertainty
associated with a single body weight measurement. The selected
method, based on the mean ADG of the poorest 50% of calves in a
strategically treated population, was assumed to provide conser-
vative estimates of the expected ADG in a healthy population hence
indicating individuals who showed an ADG below this expectation.
As expected, all of the simulated TST regimens improved weight
gains and reduced most (but not all) measures of parasitism
compared with an untreated herd. The methods used for selection
and their determinant criteria predicted different outcomes and
therefore each is addressed separately.
4.1. TST based on herd percentages
A comparison of the impact (upon various traits) of treating 10,
25, 50 or 100% of calves according to the determinant trait ADG is
provided in Fig. 2. Upon treating 100% of the population individuals
experienced a temporary elimination of parasitological burden, but
later displayed a rebound effect ea steep rise in infection. This
rebound effect was a consequence of a reduced rate of immune
acquisition due to a reduction in antigen exposure in the treated
individuals. Results for partial treatment of the herd were essen-
tially weighted averages of the untreated and treated predictions.
As a consequence of reduced WBs the treated individuals experi-
enced reduced protein loss and increased feed intake (due to
reduced immune acquisition), hence resulting in greater average
EBWs when a greater percentage of calves were treated. Larger
calves with larger feed intake requirements consumed higher
quantities of grass, and therefore a greater proportion of the larvae
on pasture. Consequently, large numbers of susceptible larvae were
removed from pasture and killed by anthelmintic activity, whereas
resistant larvae removed from pasture survived within the host to
produce eggs. This selective process tended to reduce PC but
enriched the fraction of resistant eggs excreted to pasture. There-
fore the frequency of R alleles increased as a greater percentage of
calves was selected for anthelmintic treatment. Overall it was
predicted that treating fewer calves provided the greatest overall
beneﬁtasreﬂected in BPR (Fig. 3). This ﬁnding is similar to what has
been found when modelling similar TST for lambs (Gaba et al.,
2010; Laurenson et al., 2013).
Selection for treatment according to each determinant criterion
was compared with random selection on the basis of cumulative
FEC, reduction in EBW (relative to non-parasitised group), fre-
quency of R on pasture and BPR (Fig. 3). Determinant criteria of ADG
and FEC resulted in reduced cumulative FEC compared with
random selection, either through a direct effect on eggs or via the
impact of calf size on volume of faeces produced (hence concen-
tration of eggs in faeces). Little absolute difference in reduction in
EBW gain (relative to non-parasitised group) was observed be-
tween different determinant criteria; however ADG resulted in the
largest average reduction in EBW gain. Dissection of the model
components revealed this to be a result of varied intrinsic growth
rates within the population; a portion of those selected for treat-
ment on the basis of low ADG were intrinsically slow growers and
not impeded by parasitism. Additionally a portion of the calves
experiencing large reductions in ADG did not receive treatment as
they were intrinsically fast growers and their ADG did not fall
below that of non-parasitised intrinsically slow growers. Although
determinant criteria of ADG and FEC resulted in treatment to many
of the same individuals, FEC showed the greatest improvements in
EBW. This was due to treatment of intrinsically fast growers
impeded by parasitism and a lack of treatments to intrinsically slow
growers showing few signs of parasitism. Unlike EBW the deter-
minant criteria substantially impacted on the frequency of R, and
therefore BPR. The most efﬁcient strategy was to treat calves with
the greatest WB, which suffer the greatest parasite-related loss of
productivity, whilst due to density-dependent effects and immune
response are contributing less to the aggregate herd excretion of
eggs (Michel et al., 1978; Smith et al., 1987). Calves with lower WB
may nevertheless have high FEC, and it is advantageous to allow
them to continue producing susceptible eggs while their perfor-
mance is not as severely affected by WB. According to this rationale,
pepsinogen selection was the best method to identify the optimal
treatment group, whereas ADG and FEC tend to exclude optimal
candidates: ADG by selecting intrinsic slow-growers with low WB,
and FEC by selecting low to moderately infected calves showing
Interactions between the percentage of calves treated and the
determinant criteria used for selection were predicted for BPR
(Fig. 3). The largest difference in BPR value between determinant
criteria was observed when a smaller percentage of calves were
treated. For all determinant criteria, treating 10% of the population
resulted in the largest variation in BPR values across different calf
populations. This implies a greater range of possible outcomes
associated with treating fewer calves. Interactions were not
observed between treatment percentage and determinant criteria,
simulations suggest that these selection criteria of FEC and ADG are
counter-productive compared with random or pepsinogen based
selection because of their more detrimental effect on refugia for
reasons discussed above.
4.2. TST based on threshold values
TST based on threshold triggers appeared to show the reverse
pattern in terms of the most beneﬁcial determinant criterion
compared with treating a ﬁxed percentage of the population
(Fig. 5). Treating calves according to thresholds for ADG showed by
far the greatest beneﬁt; this was followed by FEC, combined FEC
and pepsinogen, and pepsinogen alone. This pattern can be
explained by the observations of Fig. 4. Although the modelled
treatment for selection according to ADG required the highest
number of treatments, the development of resistance remained
low. This is explained by a combination of factors: ﬁrst, the
Fig. 5. Beneﬁt per R (BPR) simulated at the end of the grazing season (day 180) on a
population basis for each of the simulated control strategies; BPR represents the
beneﬁt in empty bodyweight gain (kg) per change in frequency of R on pasture, so the
higher the value the more beneﬁcial the strategy is perceived to be. Ten discrete
populations of calves were simulated on pasture initially contaminated with 200L
DM grass for calves treated strategically with ivermectin at 3, 8 and 13 weeks post-
turnout or according to threshold values of average daily bodyweight gain (ADG, kg/
d), faecal egg count (FEC, eggs/g), pepsinogen or a combination of FEC and pepsinogen.
Statistical comparisons were made between groups and are reported within the text.
Z. Berk et al. / International Journal for Parasitology: Drugs and Drug Resistance 6 (2016) 258e271 267
tendency for this method to select calves with an intrinsically slow
growth genotype that do not necessarily have high WB. Second, the
method does not select tolerant individuals (i.e. individuals in
which infection is not limited but negative ﬁtness consequences are
offset), experiencing large WBs without showing clear signs of poor
performance due to parasitism. The former resulted in only small
numbers of resistant alleles contributing to pasture, whereas the
latter allowed large numbers of susceptible eggs contributing to
Treatment according to FEC had similar effects on PC. Simula-
tions showed FEC was highest early in the grazing season, meaning
that selection according to FEC resulted in the majority of treat-
ments administered early in the season, preventing the build-up of
PC. Conversely, WBs began to rise towards the latter stages of the
grazing season in tandem with the expected mid-season rise in PC,
causing elevated pepsinogen levels. This resulted in large numbers
of treatments administered in unison, therefore causing sudden
reductions in WB and PC. Although the EBW recovered, this had
signiﬁcant implications for the frequency of R on pasture. Due to a
lack of correlation between WBs (represented here by pepsinogen
levels) and FEC there were very few individuals selected for treat-
ment based on the combined criteria of pepsinogen and FEC.
However, in this case, greater variation was observed in the BPR
between simulated populations than for other determinant criteria.
4.3. Comparison of strategies
Upon assessing the best determinant criterion for the two
described methods of selection for treatment contrasting patterns
were observed. ADG was the best determinant criterion for treating
individuals who cross a given threshold for treatment, in accor-
dance with previous work on sheep (Cabaret et al., 2006; Greer
et al., 2009; Chylinski et al., 2015). However, ADG was the worst
determinant criterion when treating a ﬁxed percentage of the
population, in accordance with Laurenson et al. (2013). This para-
doxical difference between methods can be explained by the fre-
quency and timing of treatment assessments. When treating calves
according to threshold triggers more frequent assessments were
made, ADG was a good early indicator of infection and hence by
assessing individuals more frequently infection can be caught in
the early stages preventing further reductions in ADG or the
accumulation of PC. Only two assessments were made when
treating ﬁxed percentages of the population; by the second
assessment treating calves that displayed the largest reductions in
ADG had in general developed a strong immunity, implying little
beneﬁt was gained from treatment. Alternatively pepsinogen was
the best criterion when treating a ﬁxed percentage of calves, but the
worst when treating individuals according to a threshold trigger.
Pepsinogen relates closely to WB and abomasal damage providing a
good indicator of individuals that are heavily parasitised and
display a lack of immunity, and would therefore beneﬁt from
treatment (Jennings et al., 1966; Armour and Bruce, 1974; Armour
et al., 1979). However, this made pepsinogen a poor indicator
when treating according to threshold triggers, being less effective
than other determinant criteria at preventing a build-up of PC.
4.4. Qualitative validation
Where possible, comparisons were made between model pre-
dictions and reported experimental studies. Threshold trigger
values for the determinant criteria of ADG and combined FEC and
pepsinogen have been tested experimentally (Greer et al., 2010;
McAnulty et al., 2011; H€
oglund et al., 2013; O'Shaughnessy et al.,
2014a, 2015a; b). The model predicted treating calves according
to threshold triggers for ADG to be the most beneﬁcial strategy, in
agreement with H€
oglund et al. (2009) who conducted a retro-
spective study on the feasibility of different TST determinant
criteria and concluded ADG to be the most promising. In subse-
quent studies conducted to corroborate this prediction, Greer et al.
(2010) made comparisons of two farms of dairy calves treated ac-
cording to threshold triggers of ADG versus calves receiving routine
treatment, with assessments made at monthly intervals. For groups
treated according to TST, an average of 0.83 and 1.76 anthelmintic
treatments per calf were required for the two farms respectively,
representing an 84% and 65% reduction in anthelmintic usage
compared to the control group. On both farms the TST groups
showed larger within-group variations in bodyweight along with a
reduction in ADG of 6% and 4% comparative to the control group
routinely treated at monthly intervals. These observations relate
well to model predictions: the simulated TST using threshold
triggers of ADG required 1.72 treatments per calf and showed a 5%
reduction in ADG relative to a non-parasitised calf. To make these
comparisons on reduction in ADG it was necessary to assume that
the experimental control group (given routine monthly treatment)
showed similar ADG to what would be expected of a healthy calf.
The method of Greer et al. (2010) was repeated by McAnulty et al.
(2011) for two herds. Comparable to Greer et al. (2010) the ﬁrst herd
required 1.4 treatments per calf resulting in a 74% reduction in
anthelmintic usage and a 5% reduction in ADG relative to the
control group of calves (given routine monthly treatment), sup-
porting model outputs. However, the outcomes on the second herd
was less agreeable with model predictions; 3.7 treatments were
required per calf representing a 47% reduction in anthelmintic us-
age and reductions in ADG of 2% relative to the control group were
achieved, emphasising the difﬁculty of making quantitative com-
parisons even when the same strategy is applied.
Further studies using ADG as a threshold trigger have been
conducted for beef cattle. H€
oglund et al. (2013) compared ﬁrst
grazing season bull calves subject to different treatment strategies.
Calves were left untreated, routinely treated every 4 weeks, or
treated by TST when the ADG was inferior to the ADG averaged over
the poorest growing 50% of calves in the group receiving routine
treatment every 4 weeks. A total of 0.6 treatments per calf were
required, a 92% reduction in anthelmintic usage when compared
with the control group. In general the experimental TST group
showed bodyweight gains intermediate to those of untreated and
routinely treated groups, but similar FEC to the untreated group.
Similar patterns were also predicted by the model; when compared
with untreated calves the TST group showed very similar FECs but
an improved ADG, although the simulated reductions in body-
weight gain were not always as extreme as those observed in the
No studies exist investigating the sole use of FEC or pepsinogen
as a trait for TST. Recent studies by O'Shaughnessy (2014a; 2015a;
2015b) have looked at implementing TST using combined pepsin-
ogen and FEC thresholds, often with a third condition for treatment
based on the presence of lungworm. In all studies a control group
treated three times was included for comparison. O'Shaughnessy
et al. (2014a; 2015b) found that no individuals reached both FEC
and pepsinogen levels large enough to trigger threshold treatment.
Similar to these studies the model predicted very low numbers of
treatments required with 0.05 treatments needed per calf. How-
ever, O'Shaughnessy et al. (2015a) found 1.5 treatments were
required per calf, a 50% reduction in anthelmintic usage of the
control group, although only 0.5 were as a result of O. ostertagi
markers with the majority due to lungworm.Although the reported
studies are in good general agreement, there are many confounding
variables and only qualitative comparison can be made. Model
predictions are subject to the inﬂuence of factors such as climatic
conditions, nutrition, management practices, presence of other
Z. Berk et al. / International Journal for Parasitology: Drugs and Drug Resistance 6 (2016) 258e271268
infectious agents and the level of drug resistance, not all of which
are described in the reported studies. For example, the low number
of treatments required in the studies by O'Shaughnessy et al.
(2014a; 2015b) was hypothesised to be a result of the low level
PC experienced throughout the ﬁeld trials. Additionally, many of
the control groups used in these studies represented more frequent
treatments than would be recommended in practice (H€
et al., 2013).
The developed model gives a detailed analysis of various control
strategies formulated to ensure continued effective control of
parasitism in the future, providing valuable insights that were
previously absent in literature and considerable support for treat-
ing calves according toTST. Support was provided for treating fewer
calves to help maintain refugia and more strongly for treating calves
according to threshold trigger values, in particular for the deter-
minant criterion ADG. Trigger thresholds may be considered more
applicable across infection levels. For example, over-treatment of
herds exposed to very low levels infections may be reduced.
Treating according to ADG is beneﬁcial not only in terms of treat-
ment success, but also for ease of practical implementation. How-
ever, the modelled trigger threshold for ADG was calculated based
on growth rates of their strategically treated counterparts. In
practice a group of strategically treated calves would not be kept to
calculate this threshold level. One way of overcoming this is by
looking at growth trajectories of individual animals and treat ani-
mals that deviate from their own trajectory.
In order for these strategies to be adopted farmers must be
convinced of the merits of TST. In practice, the implementation of
TST on cattle farms requires further optimisation, cost-beneﬁt
analysis, and attention to practical issues related to assessment of
individuals for treatment. The most feasible option is treatment
according to ADG as measurements are instantaneous with fewer
additional diagnostic costs. Although currently weighing scales are
expensive, individual weighing is labour intensive and poses risk of
injury to both cattle and humans, the rapid advances in precision
farming may change all these (Laca, 2009). Nevertheless,
convincing farmers to convert to TST strategies may not be
straightforward, as has been suggested for sheep, especially
because the beneﬁts from reducing the rate of anthelmintic resis-
tance development may not be immediately obvious. The relative
advantage, complexity and compatibility of TST strategies are all
important factors taken into consideration by the farming industry
(for which varied priorities exist) (Woodgate and Love, 2012). Dif-
ﬁculties in quantifying such factors make it challenging for farmers
to visualise the problem and subsequent beneﬁts of TST, steps to-
wards quantifying these are essential as change is more likely to be
adopted when the problem is obvious (Rogers, 1995). Dealing with
this challenge, constitutes a new ﬁeld of research that requires the
collaboration between parasitologists and social scientists.
Our model focused on a ﬁrst grazing season over 6 months
however, many calves are kept for a second grazing season or more.
Extension of the model to simulate calves over multiple grazing
seasons would provide insights into the implementation of these
strategies over a longer period. At the end of the ﬁrst grazing season
treatment strategies will have different effects on factors such as
ﬁnal PC, hypobiosis and immunity (Claerebout et al., 1999). All
these have important implications for second grazing season calves
in terms of infection dynamics, making this an important issue to
address in terms of the sustainability of different control strategies.
Additionally, most natural infections are mixed with Cooperia sp.
which can often be more prevalent, particularly in the early stages
in the grazing season. It is difﬁcult to distinguish between species in
faecal samples, with large numbers of eggs produced by Cooperia
worms implying threshold values of FEC may not be representative
of O. ostertagi burdens. Although there does not appear to be inter-
species interactions (Kloosterman et al., 1984; Satrija and Nansen,
1993; Hilderson et al., 1995) there are important consequences
for levels of protein loss, hence modiﬁcation of the model to ac-
count for Cooperia would prove beneﬁcial in future development.
In the model we developed a relationship between ivermectin
activity, an anthelmintic widely used in cattle in the UK (Barton
et al., 2006), and different O. ostertagi genotypes. This was
required to determine the effect of treatment on the frequency of
resistance alleles (R) within the nematode population. There is now
strong evidence that the mechanism for ivermectin is complex and
controlled by many alleles at separate loci (Gilleard, 2006; Prichard,
2007; Kotze et al., 2014). To avoid model complexity anthelmintic
resistance was assumed to be conferred by two independent genes.
There are many unknown factors inﬂuencing the rate of anthel-
mintic resistance, for example the number of relevant alleles, the
relative importance of various alleles (on drug efﬁcacy and persis-
tence activity), level of pre-existing alleles and the relative ﬁtness of
alleles on pasture (or within an untreated host), amongst others.
Should alterations be made to these parameters it would be ex-
pected that the rate at which anthelmintic resistance develops
would be affected (Barnes et al., 1995; Leathwick, 2013), although
the same general principles and patterns would be expected to
apply. For example, little indication exists in the literature as to the
ﬁtness of each genotype either on pasture or against anthelmintic
treatment. Upon modelling a ﬁtness cost associated with R alleles
(either on pasture or within an untreated host) it was observed that
the development of resistance was slowed, however the same
general patterns were observed. Ultimately, the aim of the model
was not to accurately predict the rate at which resistance occurs,
but rather to compare the relative effect of a range of control
In conclusion, we have developed a simulation model that ap-
pears to be capable of predicting the consequences of TST on the
performance and development of nematode resistance amongst
calf populations. We suggest that the utility of the model is such
that allows it to be extended to consider other strategies for
reduction of the development of resistance, including different
parasite species and host genotypes and variation in climatic in-
ﬂuences on larval availability and grass growth.
Funding was provided by the Biotechnology and Biological Sci-
ences Research Council (BBSRC) of the UK and Merial, France (Grant
Agriculture &Horticulture Development Board (AHDB), 2013. http://beefandlamb.
strategies-manual-8-150716.pdf [Accessed October 2016].
Allen, W., Sweasey, D., Berret, S., Nancy Hebert, C., Patterson, D., 1970. Clinical pa-
thology of ostertagiasis in calves during prolonged experimental infection.
J. Comp. Path 80, 441e454.
Almería, S., Llorente, M.M., Uriarte, J., 1996. Monthly ﬂuctuations of worm burdens
and hypobiosis of gastrointestinal nematodes of calves in extensive manage-
ment systems in the Pyrenees (Spain). Vet. Parasitol. 67, 225e236.
Anderson, N., Armour, J., Rosalind, M.E., Jarrett, W.F.H., Jennings, F.W., Ritchie, J.S.D.,
Urquhart, G.M., 1966. Experimental Ostertagia ostertagi infections in calves:
results of single infections with ﬁve graderd dose levels of larvae. Am. J. Vet.
Res. 27, 1259e1265.
Areskog, M., Sollenberg, S., Engstr€
om, A., von Samson-Himmelstjerna, G.,
oglund, J., 2013. A controlled study on gastrointestinal nematodes from two
Swedish cattle farms showing ﬁeld evidence of ivermectin resistance. Parasit.
Vectors 7, 13.
Armour, J., Bairden, K., Batty, A.F., Davidson, C.C., Ross, D.B., 1985. Persistent
Z. Berk et al. / International Journal for Parasitology: Drugs and Drug Resistance 6 (2016) 258e271 269
anthelmintic activity of ivermectin in cattle. Vet. Rec. 116, 151e153.
Armour, J., Bairden, K., Duncan, J.L., Jennings, F.W., Parkins, J.J., 1979. Observations
on ostertagiasis in young cattle over two grazing seasons with special reference
to plasma pepsinogen levels. Vet. Rec. 105, 500e503.
Armour, J., Bruce, R.G., 1974. Inhibited development in Ostertagia ostertagi
infectionsea diapause phenomenon in a nematode. Parasitology 69, 161e174.
Baker, D.G., Gershwin, L.J., 1993. Inverse relationship between IgE and worm bur-
dens in cattle infected with Ostertagia ostertagi. Vet. Parasitol. 47, 87e97.
Barnes, E.H., Dobson, R.J., 1990. Population dynamics of Trichostrongylus colu-
brimformis in sheep: computer model to simulate grazing systems and the
evolution of anthelmintic resistance. Int. J. Parasitol. 20, 823e831.
Barnes, E.H., Dobson, R.J., Barger, I. a, 1995. Worm control and anthelmintic resis-
tance: adventures with a model. Parasitol. Today 11, 56e63.
Barton, C.H.J., Dale, E.F., Dixon, C., Coles, G.C., 2006. Short Communications Survey of
parasite control on beef farms in south-west England. Vet. Parasitol. 159,
Berk, Z., Bishop, S.C., Forbes, A.B., Kyriazakis, I., 2016a. A simulation model to
investigate interactions between ﬁrst season grazing calves and Ostertagia
ostertagi. Vet. Parasitol. 226, 198e209.
Berk, Z., Laurenson, Y.C.S.M., Forbes, A.B., Kyriazakis, I., 2016b. A stochastic model to
investigate the effects of control strategies on calves exposed to Ostertagia
ostertagi. Parasitology 143, 1755e1772 . http://dx.doi.org/10.1017/
Besier, R.B., 2012. Refugia-based strategies for sustainable worm control: factors
affecting the acceptability to sheep and goat owners. Vet. Parasitol. 186, 2e9.
Borgsteede, F.H., Hendriks, J., 1986. The residual effect of treatment with ivermectin
after experimental reinfection with nematodes in calves. Vet. Q. 8, 98e104 .
Cabaret, J., Silvestre, A., Cortet, J., Sauve, C., 2006. Nematode targeted selective
treatments in lambs under temperate climate using weight gains, anaemia or
diarrhoea scores. In: ICOPA XId11th International Congress of Parasitology,
Glasgow (UK), 6e11 August 2006.
Cammack, K.M., Leymaster, K. a, Jenkins, T.G., Nielsen, M.K., 2005. Estimates of
genetic parameters for feed intake, feeding behavior, and daily gain in com-
posite ram lambs. J. Anim. Sci. 83, 777e785.
Charlier, J., Morgan, E.R., Rinaldi, L., Dijk, J. Van, Demeler, J., H€
Hertzberg, H., Ranst, B. Van, Hendrickx, G., Vercruysse, J., Kenyon, F., 2014.
Review Practices to optimise gastrointestinal nematode control on sheep, goat
and cattle farms in Europe using targeted (selective) treatments. Vet. Rec. 175,
Chylinski, C., Cortet, J., Neveu, C., Cabaret, J., 2015. Exploring the limitations of
pathophysiological indicators used for targeted selective treatment in sheep
experimentally infected with Haemonchus contortus. Vet. Parasitol. 207,
Claerebout, E., Dorny, P., Agneessens, J., Demeulenaere, D., Vercruysse, J., 1999. The
effect of ﬁrst season chemoprophylaxis in calves on second season pasture
contamination and acquired resistance and resilience to gastrointestinal nem-
atodes. Vet. Parasitol. 80, 289e301.
Claerebout, E., Vercruysse, J., 2000. The immune response and the evaluation of
acquired immunity against gastrointestinal nematodes in cattle: a review.
Parasitology 120 (Suppl. l), S25eS42.
Coop, R.L., Kyriazakis, I., 1999. Nutrition-parasite interaction. Vet. Parasitol. 84,
Demeler, J., Kuttler, U., von Samson-Himmelstjerna, G., 2010. Adaptation and
evaluation of three different in vitro tests for the detection of resistance to
anthelmintics in gastro intestinal nematodes of cattle. Vet. Parasitol.170, 61e70.
Doeschl-Wilson, A., Vagenas, D., Kyriazakis, I., Bishop, S., 2008. Exploring the as-
sumptions underlying genetic variation in host nematode resistance. Genet. Sel.
Dorny, P., Shaw, D.J., Vercruysse, J.,1999. The determination at housing of exposure
to gastrointestinal nematode infections in ﬁrst-grazing season calves. Vet.
Parasitol. 80, 325e340.
Dorny, P., Vercruysse, J., Hilderson, H., Berghen, P., Van Ommeslaeghe, K.,
Kloosterman, A., 1988. Field evaluation of an experimental albendazole pulse
release bolus in the control of parasitic gastroenteritis in ﬁrst-season grazing
calves. Vet. Res. Commun. 12, 335e342.
Eddi, C., Muniz, R. a., Caracostantogolo, J., Errecalde, J.O., Rew, R.S., Michener, S.L.,
McKenzie, M.E., 1997. Comparative persistent efﬁcacy of doramectin, ivermectin
and fenbendazole against natural nematode infections in cattle. Vet. Parasitol.
Edmonds, M.D., Johnson, E.G., Edmonds, J.D., 2010. Anthelmintic resistance of
Ostertagia ostertagi and Cooperia oncophora to macrocyclic lactones in cattle
from the western United States. Vet. Parasitol. 170, 224e229.
El-Abdellati, A., Charlier, J., Geldhof, P., Levecke, B., Demeler, J., 2010. The use of a
simpliﬁed faecal egg count reduction test for assessing anthelmintic efﬁcacy on
Belgian and German cattle farms. Vet. Parasitol. 169, 352e357.
Forbes, A.B., Huckle, C.A., Gibb, M.J., Rook, A.J., Nuthall, R., 2000. Evaluation of the
effects of nematode parasitism on grazing behaviour, herbage intake and
growth in young grazing cattle. Vet. Parasitol. 90, 111e118.
Fox, M.T., 1993. Pathophysiology of infection with Ostertagia ostertagi in cattle. Vet.
Parasitol. 46, 143e158.
Fox, M.T., Gerrelli, D., Pitt, S.R., Jacobs, D.E., Gill, M., Gale, D.L., 1989. Ostertagia
ostertagi infection in the calf: effects of a trickle challenge on appetite, di-
gestibility, rate of passage of digesta and liveweight gain. Res. Vet. Sci. 47,
Fox, M.T., Gerrelli, D., Pitt, S.R., Jacobs, D.E., Hart, I.C., Simmonds, a D., 1987.
Endocrine effects of a single infection with Ostertagia ostertagi in the calf. Int. J.
Parasitol. 17, 1181e1185 .
Gaba, S., Cabaret, J., Sauv
e, C., Cortet, J., Silvestre, A., 2010. Experimental and
modeling approaches to evaluate different aspects of the efﬁcacy of targeted
selective treatment of anthelmintics against sheep parasite nematodes. Vet.
Parasitol. 171, 254e262.
Gilleard, J.S., 2006. Understanding anthelmintic resistance: the need for genomics
and genetics. Int. J. Parasitol. 36, 1227e1239.
Gilleard, J.S., Beech, R.N., 2007. Population genetics of anthelmintic resistance in
parasitic nematodes. Parasitology 134, 1133e1147.
Greer, A.W., Kenyon, F., Bartley, D.J., Jackson, E.B., Gordon, Y., Donnan, a. a.,
McBean, D.W., Jackson, F., 2009. Development and ﬁeld evaluation of a decision
support model for anthelmintic treatments as part of a targeted selective
treatment (TST) regime in lambs. Vet. Parasitol. 164, 12e20.
Greer, A.W., Mcanulty, R.W., Gibbs, S.J., 2010. Performance-based targeted selective
anthelmintic treatment regime for grazing dairy calves. Proc. 4th Australas.
Dairy Sci. Symp 385e389.
Hilderson, H., Berghen, P., Vercruysse, J., Dorny, P., Braem, L., 1989. Diagnostic value
of pepsinogen for clinical ostertagiosis. Vet. Rec. 125, 376e377.
Hilderson, H., Vercruysse, J., Claerebout, E., De Graaf, D.C., Fransen, J., Berghen, F.P.,
1995. Interactions between Ostertagia ostertagi and Cooperia oncophora in
calves. Vet. Parasitol. 56, 107e119.
Hilderson, H., Vercruysse, J., Dorny, P., Berghen, P., Kloosterman, A.,1990. Subclinical
parasitism in calves: biochemical and serological evaluation of preventive
treatment against gastroenteritis and husk. Prev. Vet. Med. 8, 283e290.
oglund, J., Dahlstr€
om, F., Sollenberg, S., Hessle, A., 2013. Weight gain-based tar-
geted selective treatments (TST) of gastrointestinal nematodes in ﬁrst-season
grazing cattle. Vet. Parasitol. 196, 358e365.
oglund, J., Morrison, D. a, Charlier, J., Dimander, S.-O., Larsson, A., 2009. Assessing
the feasibility of targeted selective treatments for gastrointestinal nematodes in
ﬁrst-season grazing cattle based on mid-season daily weight gains. Vet. Para-
sitol. 164, 80e88.
Jabbar, A., Iqbal, Z., Kerboeuf, D., Muhammad, G., Khan, M.N., Afaq, M., 2006.
Anthelmintic resistance: the state of play revisited. Life Sci. 79, 2413e2431.
Jennings, F.W., Armour, J., Lawson, D.D., Roberts, R., 1966. Experimental Ostertagia
ostertagi infections in calves: studies with abomasal cannulas. Am. J. Vet. Sci. 27,
Kahn, L., Kyriazakis, I., Jackson, F., Coop, R., 2000. Temporal effects of protein
nutrition on the growth and immunity of lambs infected with Trichostrongylus
colubriformis. Int. J. Parasitol. 30, 193e205.
Kaplan, R.M., 2004. Drug resistance in nematodes of veterinary importance: a status
report. Trends Parasitol. 20, 477e481.
Kenyon, F., Greer, a W., Coles, G.C., Cringoli, G., Papadopoulos, E., Cabaret, J.,
Berrag, B., Varady, M., Van Wyk, J. a, Thomas, E., Vercruysse, J., Jackson, F., 2009.
The role of targeted selective treatments in the development of refugia-based
approaches to the control of gastrointestinal nematodes of small ruminants.
Vet. Parasitol. 164, 3e11.
Kenyon, F., McBean, D., Greer, A.W., Burgess, C.G.S., Morrison, A. a., Bartley, D.J.,
Bartley, Y., Devin, L., Nath, M., Jackson, F., 2013. A comparative study of the
effects of four treatment regimes on ivermectin efﬁcacy, body weight and
pasture contamination in lambs naturally infected with gastrointestinal nem-
atodes in Scotland. Int. J. Parasitol. Drugs Drug Resist 3, 77e84.
Kloosterman, A., Albers, G.A.A., van den Brink, R., 1984. Negative interactions be-
tween Ostertagia ostertagi and Cooperia oncophora in calves. Vet. Parasitol. 15,
Kotze, A.C., Hunt, P.W., Skuce, P., von Samson-Himmelstjerna, G., Martin, R.J.,
Sager, H., Krücken, J., Hodgkinson, J., Lespine, A., Jex, A.R., Gilleard, J.S.,
Beech, R.N., Wolstenholme, A.J., Demeler, J., Robertson, A.P., Charvet, C.L.,
Neveu, C., Kaminsky, R., Rufener, L., Alberich, M., Menez, C., Prichard, R.K., 2014.
Recent advances in candidate-gene and whole-genome approaches to the
discovery of anthelmintic resistance markers and the description of drug/re-
ceptor interactions. Int. J. Parasitol. Drugs Drug Resist 4, 164e184.
Kyriazakis, I., 2010. Is anorexia during infection in animals affected by food
composition? Anim. Feed Sci. Technol. 156, 1e9.
Kyriazakis, I., 2014. Pathogen-induced anorexia: a herbivore strategy or an un-
avoidable consequence of infection? Anim. Prod. Sci. 54, 1190e1197.
Laca, E.A., 2009. Precision livestock production: tools and concepts. R. Bras. Zootec.
Larsson, A., Dimander, S.O., Rydzik, A., Uggla, A., Waller, P.J., H€
oglund, J., 2007. A 3-
year ﬁeld evaluation of pasture rotation and supplementary feeding to control
parasite infection in ﬁrst-season grazing cattle-Dynamics of pasture infectivity.
Vet. Parasitol. 145, 129e137.
Laurenson, Y.C.S.M., Bishop, S.C., Forbes, A.B., Kyriazakis, I., 2013. Modelling the
short- and long-term impacts of drenching frequency and targeted selective
treatment on the performance of grazing lambs and the emergence of
anthelmintic resistance. Parasitology 140, 780e791.
Laurenson, Y.C.S.M., Bishop, S.C., Kyriazakis, I., 2011. In silico exploration of the
mechanisms that underlie parasite-induced anorexia in sheep. Br. J. Nutr. 106,
Laurenson, Y.C.S.M., Kahn, L.P., Bishop, S.C., Kyriazakis, I., 2016. Which is the best
phenotypic trait for use in a targeted selective treatment strategy for growing
lambs in temperate climates? Vet. Parasitol. 226, 174e188 .
Laurenson, Y.C.S.M., Kyriazakis, I., Bishop, S.C., 2012. In silico explorationn of the
impact of pasture larvae contamination and anthelmintic treatment on genetic
parameter estimates for parasite resistance in grazing sheep. J. Anim. Sci. 90,
Z. Berk et al. / International Journal for Parasitology: Drugs and Drug Resistance 6 (2016) 258e271270
Leathwick, D.M., 2013. Managing anthelmintic resistance eparasite ﬁtness, drug
use strategy and the potential for reversion towards susceptibility. Vet. Para-
sitol. 198, 145e153.
Leathwick, D.M., Vlassofft, A., Barlow, N.D., 1995. A model for nematodiasis in New
Zealand Lambs: the effect of drenching regime and grazing management on the
development of anthelmintic resistance. Int. J.Parasitol. 25, 1479e1490.
Lifschitz, A., Virkel, G., Sallovitz, J., Sutra, J.F., Galtier, P., 2000. Comparative distri-
bution of ivermectin and doramectin to parasite location tissues in cattle Vet.
Parasitol 87, 327e338.
MATLAB and statistics toolbox release, 2015b. The Math Works, Inc., Natick, Mas-
sachusetts, United States.
McAnulty, R.W., Gibbs, S.J., Greer, A.W., 2011. BRIEF COMMUNICATION: liveweight
gain of grazing dairy calves in their ﬁrst season subjected to a targeted selective
anthelmintic treatment (TST) regime. Proc. New Zeal. Soc. Anim. Prod. 71,
Michel, J.F., Lancaster, M.B., Hong, C., 1978. The length of Ostertagia ostertagi in
populations of uniform age. Int. J. Parasitol. 8, 437e441.
Mihi, B., van Meulder, F., Vancoppernolle, S., Rinaldi, M., Chiers, K., van den
Broeck, W., Goddeeris, B.M., Vercruysse, J., Claerebout, E., Geldhof, P., 2014.
Analysis of the mucosal immune responses induced by single and trickle in-
fections with the bovine abomasal nematode Ostertagia ostertagi. Parasite
Immunol. 36, 150e156.
NOAH, 2015 (accessed November 2015). http://www.noahcompendium.co.uk/
O'Shaughnessy, J., Earley, B., Mee, J.F., Doherty, M.L., Crosson, P., Barrett, D., de
Waal, T., 2015a. Nematode control in suckler beef cattle over their ﬁrst two
grazing seasons using a targeted selective treatment approach. Ir. Vet. J. 68, 13.
O'Shaughnessy, J., Earley, B., Mee, J.F., Doherty, M.L., Crosson, P., Barrett, D., de
Waal, T., 2015b. Controlling nematodes in dairy calves using targeted selective
treatments. Vet. Parasitol. 209, 221e228.
O'Shaughnessy, J., Earley, B., Mee, J.F., Doherty, M.L., Crosson, P., Barrett, D.,
Macrelli, M., de Waal, T., 2014a. Nematode control in spring-born suckler beef
calves using targeted selective anthelmintic treatments. Vet. Parasitol. 205,
O'Shaughnessy, J., Earley, B., Mee, J.F., Doherty, M.L., Crosson, P., Barrett, D.,
Prendiville, R., Macrelli, M., de Waal, T., 2014b. Detection of anthelmintic
resistance on two Irish beef research farms. Vet. Rec. 175, 120e121.
Papadopoulos, E., Gallidis, E., Ptochos, S., 2012. Anthelmintic resistance in sheep in
Europe: a selected review. Vet. Parasitol. 189, 85e88.
Ploeger, H.W., Kloosterman, A., 1993. Gastrointestinal nematode infections and
weight gain in dairy replacement stock: ﬁrst-year calves. Vet. Parasitol. 46,
Prichard, R.K., 2007. Ivermectin resistance and overview of the consortium for
anthelmintic resistance SNPs. Expert Opin. Drug Discov. 2, S41eS52.
Ranjan, S., Trudeau, C., Prichard, R.K., Daigneault, J., Rew, R.S., 1997. Nematode
reinfection following treatment of cattle with doramectin and ivermectin. Vet.
Parasitol. 72, 25e31.
Ritchie, J.S.D., Anderson, N., Armour, J., Jarrett, W.F.H., Jennings, F.W., Urquhart, G.M.,
1966. Experimental Ostertagia ostertagi infections in calves: parasitology and
pathogenesis of a single infection. Am. J. Vet. Sci. 27, 659e667.
Rogers, E.M., 1995. Diffusion of Innovations. The Free Press, New York, USA.
Rose, H., Rinaldi, L., Bosco, a., Mavrot, F., de Waal, T., Skuce, P., Charlier, J.,
Torgerson, P.R., Hertzberg, H., Hendrickx, G., Vercruysse, J., Morgan, E.R., 2015.
Widespread anthelmintic resistance in European farmed ruminants: a sys-
tematic review. Vet. Rec. 176, 546.
Satrija, F., Nansen, P., 1993. Experimental concurrent infections with Ostertagia
ostertagi and Cooperia oncophora in the calf. Res. Vet. Sci. 55, 92e97.
Shaw, D.J., Vercruysse, J., Claerebout, E., Agneessens, J., Dorny, P., 1997. Gastroin-
testinal nematode infections of ﬁrst-season grazing calves in Belgium: general
patterns and the effect of chemoprophylaxis. Vet. Parasitol. 69, 103e116.
Shaw, D.J., Vercruysse, J., Claerebout, E., Dorny, P.,1998a. Gastrointestinal nematode
infections of ﬁrst-grazing season calves in Western Europe: general patterns
and the effect of chemoprophylaxis. Vet. Parasitol. 75, 115e131.
Shaw, D.J., Vercruysse, J., Claerebout, E., Dorny, P.,1998b. Gastrointestinal nematode
infections of ﬁrst-grazing season calves in Western Europe: associations
between parasitological, physiological and physical factors. Vet. Parasitol. 75,
Sibbald, A.M., Shellard, L.J.F., Smart, T.S., 2000. Effects of space allowance on the
grazing behaviour and spacing of sheep. Appl. Anim. Behav. Sci. 70, 49e62.
Smith, G., Grenfell, B.T., Anderson, R.M., 1987. The regulation of Ostertagia ostertagi
populations in calves: density-dependent control of fecundity. Parasitology 95,
Smith, G., Grenfell, B.T., Isham, V., Cornell, S., 1999. Anthelmintic resistance revis-
ited: under-dosing, chemoprophylactic strategies, and mating probabilities. Int.
J. Parasitol. 29, 77e94.
Snider, T.G., Williams, J.C., Sheehan, D.S., Fuselier, R.H., 1981. Plasma pepsinogen,
inhibited larval development, and abomasal lesions in experimental infections
of calves with Ostertagia ostertagi. Vet. Parasitol. 8, 173e183.
Stromberg, B.E., 1997. Environmental factors inﬂuencing transmission. Vet. Para-
sitol. 72, 247e264.
Sutherland, I.A., Bullen, S.L., 2014. Parasite controleare we at the edge of a preci-
pice? Proc. 5th Australas. Dairy Sci. Symp. 298e303.
Sutherland, I.A., Leathwick, D.M., 2011. Anthelmintic resistance in nematode para-
sites of cattle: a global issue? Trends Parasitol. 27, 176e181.
Szyszka, O., Kyriazakis, I., 2013. What is the relationship between level of infection
and “sickness behaviour”in cattle? Appl. Anim. Behav. Sci. 147, 1e10.
Toutain, P.L., Upson, D.W., Terhune, T.N., Mckenzie, M.E., 1997. Comparative phar-
macokinetics of doramectin and ivermectin in cattle. Vet. Parasitol. 72, 3e8.
Vagenas, D., Doeschl-Wilson, A., Bishop, S.C., Kyriazakis, I., 2007. In silico explora-
tion of the effects of host genotype and nutrition on the genetic parameters of
lambs challenged with gastrointestinal parasites. Int. J. Parasitol. 37, 1617e1630.
van Wyk, J.A., 2001. Refugia eoverlooked as perhaps the most potent factor con-
cerning the development of anthelmintic resistance. Onder-stepoort J. Vet. Res.
van Wyk, J.A., Hoste, H., Kaplan, R.M., Besier, R.B., 2006. Targeted selective treat-
ment for worm management-How do we sell rational programs to farmers?
Vet. Parasitol. 139, 336e346.
Vercruysse, J., Claerebout, E., 2001. Treatment vs non-treatment of helminth in-
fections in cattle: deﬁning the threshold. Vet. Parasitol. 98, 195e214.
Vercruysse, J., Dorny, P., Claerebout, E., Demeulenaere, D., Smets, K., Agneessens, J.,
2000. Evaluation of the persistent efﬁcacy of doramectin and ivermectin
injectable against Ostertagia ostertagi and Cooperia oncophora in cattle. Vet.
Parasitol. 56, 63e69.
Vercruysse, J., Hilderson, H., Dorny, P., Berghen, P., 1988. Efﬁcacy of early season
anthelmintic treatment against gastrointestinal nematodes. Vet. Q. 10,
Verschave, S.H., Levecke, B., Duchateau, L., Vercruysse, J., Charlier, J., 2015.
Measuring larval nematode contamination on cattle pastures: comparing two
herbage sampling methods. Vet. Parasitol. 210, 159e166.
Verschave, S.H., Vercruysse, J., Claerebout, E., Rose, H., Morgan, E.R., Charlier, J.,
2014. The parasitic phase of Ostertagia ostertagi : quantiﬁcation of the main life
history traits through systematic review and meta-analysis. Int. J. Parasitol. 44,
1091 e1104 .
Williams, J.C., Broussard, S.D., 1995. Persistent anthelmintic activity of ivermectin
against gastrointestinal nematodes of cattle. Am. J. Vet. Res. 56, 1169e1175 .
Williams, J.C., Knox, J.W., Marbury, K.S., Kimball, M.D., Baumann, B. a, snider, T.G.,
1987. The epidemiology of Ostertagia ostertagi and other gastrointestinal
nematodes of cattle in Louisiana. Parasitology 95, 135e153.
Woodgate, R.G., Love, S., 2012. WormKill to WormBoss-Can we sell sustainable
sheep worm control? Vet. Parasitol. 186, 51e57.
Wolstenholme, A.J., Fairweather, I., Prichard, R., Samson-Himmelstjerna, G. Von,
Sangster, N.C., 2004. Drug resistance in veterinary helminths. Trends Parasitol.
Yazwinski, T.A., Tucker, C.A., Powell, J., Reynolds, J., Hornsby, P., Johnson, Z., 2009.
Fecal egg count reduction and control trial determinations of anthelmintic ef-
ﬁcacies for several parasiticides utilizing a single set of naturally infected calves.
Vet. Parasitol. 164, 232e241.
Yazwinski, T.A., Tucker, C.A., Wray, E., Jones, L., Reynolds, J., Hornsby, P., Powell, J.,
2013. Control trial and fecal egg count reduction test determinations of
nematocidal efﬁcacies of moxidectin and generic ivermectin in recently
weaned, naturally infected calves. Vet. Parasitol. 195, 95e101.
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