Nematode parasites of sheep: extension of a simple model to include host variability

Novel epidemiological model of gastrointestinal nematode infection to assess grazing cattle resilience by integrating host growth, parasite, grass and environmental dynamics

Gastrointestinal nematode (GIN) infections are ubiquitous and often cause morbidity and reduced performance in livestock. Emerging anthelmintic resistance and increasing change in climate patterns require evaluation of alternatives to traditional treatment and management practices. Mathematical models of parasite transmission between hosts and the environment have contributed towards the design of appropriate control strategies in ruminants, but have yet to account for relationships between climate, infection pressure, immunity, resources, and growth. Here, we develop a new epidemiological model of GIN transmission in a herd of grazing cattle, including host tolerance (body weight and feed intake), parasite burden and acquisition of immunity, together with weather-dependent development of parasite free-living stages, and the influence of grass availability on parasite transmission. Dynamic host, parasite and environmental factors drive a variable rate of transmission. Using literature sources, the model was parametrised for Ostertagia ostertagi, the prevailing pathogenic GIN in grazing cattle populations in temperate climates. Model outputs were validated on published empirical studies from first season grazing cattle in northern Europe. These results show satisfactory qualitative and quantitative performance of the model; they also indicate the model may approximate the dynamics of grazing systems under co-infection by O. ostertagi and Cooperia oncophora, a second GIN species common in cattle. In addition, model behaviour was explored under illustrative anthelmintic treatment strategies, considering impacts on parasitological and performance variables. The model has potential for extension to explore altered infection dynamics as a result of management and climate change, and to optimise treatment strategies accordingly. As the first known mechanistic model to combine parasitic and free-living stages of GIN with host feed-intake and growth, it is well suited to predict complex system responses under non-stationary conditions. We discuss the implications, limitations and extensions of the model, and its potential to assist in the development of sustainable parasite control strategies.

Assessing Goats' Fecal Avoidance Using Image Analysis-Based Monitoring

The recent advances in sensor technologies and data analysis could improve our capacity to acquire long-term and individual dataset on animal behavior. In livestock management, this is particularly interesting when behavioral data could be linked to production performances, physiological or genetical information, with the objective of improving animal health and welfare management. In this study, we proposed a framework, based on computer vision and deep learning, to automatically estimate animal location within pasture and discuss the relationship with the risk of gastrointestinal nematode (GIN) infection. We illustrated our framework for the monitoring of goats allowed to graze an experimental plot, where feces containing GIN infective larvae were previously dropped in delimited areas. Four animals were monitored, during two grazing weeks on the same pasture (week 1 from April 12 to 19, 2021 and week 2, from June 28 to July 5, 2021). Using the monitoring framework, different components of animal behavior were analyzed, and the relationship with the risk of GIN infection was explored. First, in average, 87.95% of the goats were detected, the detected individuals were identified with an average sensitivity of 94.9%, and an average precision of 94.8%. Second, the monitoring of the ability of the animal to avoid infected feces on pasture showed an important temporal and individual variability. Interestingly, the avoidance behavior of 3 animals increased during the second grazing week (Wilcoxon rank sum, p-value < 0.05), and the level of increase was correlated with the level of infection during week 1 (Pearson's correlation coefficient = 0.9). The relationship between the time spent on GIN-infested areas and the level of infection was also studied, but no clear relationship was found. In conclusion, due to the low number of studied animals, biological results should be interpreted with caution; nevertheless, the framework provided here is a new relevant tool to explore the relationship between ruminant behavior and GIN parasitism in experimental studies.

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

Targeted selective treatment (TST) requires the ability to identify the animals for which anthelmintic treatment will result in the greatest benefit to the entire flock. Various phenotypic traits have previously been suggested as determinant criteria for TST; however, the weight gain benefit and impact on anthelmintic efficacy for each determinant criterion is expected to be dependent upon the level of nematode challenge and the timing of anthelmintic treatment. A mathematical model was used to simulate a population of 10,000 parasitologically naïve Scottish Blackface lambs (with heritable variation in host-parasite interactions) grazing on medium-quality pasture (grazing density=30 lambs/ha, crude protein=140g/kg DM, metabolisable energy=10MJ/kg DM) with an initial larval contamination of 1000, 3000 or 5000 Teladorsagia circumcincta L3/kg DM. Anthelmintic drenches were administered to 0, 50 or 100% of the population on a single occasion. The day of anthelmintic treatment was independently modelled for every day within the 121day simulation. Where TST scenarios were simulated (50% treated), lambs were either chosen by random selection or according to highest faecal egg count (FEC, eggs/g DM faeces), lowest live weight (LW, kg) or lowest growth rate (kg/day). Average lamb empty body weight (kg) and the resistance (R) allele frequency amongst the parasite population on pasture were recorded at slaughter (day 121) for each scenario. Average weight gain benefit and increase in R allele frequency for each determinant criterion, level of initial larval contamination and day of anthelmintic treatment were calculated by comparison to a non-treated population. Determinant criteria were evaluated according to average weight gain benefit divided by increase in R allele frequency to determine the benefit per R. Whilst positive phenotypic correlations were predicted between worm burden and FEC; using LW as the determinant criterion provided the greatest benefit per R for all levels of initial larval contamination and day of anthelmintic treatment. Hence, LW was identified as the best determinant criterion for use in a TST regime. This study supports the use of TST strategies as benefit per R predictions for all determinant criteria were greater than those predicted for the 100% treatment group, representing an increased long-term productive benefit resulting from the maintenance of anthelmintic efficacy. Whilst not included in this study, the model could be extended to consider other parasite species and host breed parameters, variation in climatic influences on larval availability and grass growth, repeated anthelmintic treatments and variable proportional flock treatments.

Modelling gastrointestinal parasitism infection in a sheep flock over two reproductive seasons: in silico exploration and sensitivity analysis

In reproducing ewes, a periparturient breakdown of immunity is often observed to result in increased fecal egg excretion, making them the main source of infection for their immunologically naive lambs. In this study, we expanded a simulation model previously developed for growing lambs to explore the impact of the genotype (performance and resistance traits) and host nutrition on the performance and parasitism of both growing lambs and reproducing ewes naturally infected with Teladorsagia circumcincta. Our model accounted for nutrient-demanding phases, such as gestation and lactation, and included a supplementary module to manage the age structure of the ewe flock. The model was validated by comparison with published data. Because model parameters were unknown or poorly estimated, detailed sensitivity analysis of the model was performed for the sheep mortality and the level of infection, following a preliminary screening step. The parameters with the greatest effect on parasite-related outputs were those driving animal growth and milk yield. Our model enables different parasite-control strategies (host nutrition, breeding for resistance and anthelmintic treatments) to be assessed on the long term in a sheep flock. To optimize in silico exploration, the parameters highlighted by the sensitivity analysis should be refined with real data.

A simulation model to investigate interactions between first season grazing calves and Ostertagia ostertagi

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A deterministic model to address calf—O. ostertagi interactions was developed.

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The model predicts performance and FEC for different infection intensities.

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It performs well when validated against published data.

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It does not account for calf genotypic variation.

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A future aim is to develop a stochastic model to account for between host variation.

A dynamic, deterministic model was developed to investigate the consequences of parasitism with Ostertagia ostertagi, the most prevalent and economically important gastrointestinal parasite of cattle in temperate regions. Interactions between host and parasite were considered to predict the level of parasitism and performance of an infected calf. Key model inputs included calf intrinsic growth rate, feed quality and mode and level of infection. The effects of these varied inputs were simulated on a daily basis for key parasitological (worm burden, total egg output and faecal egg count) and performance outputs (feed intake and bodyweight) over a 6 month grazing period. Data from published literature were used to parameterise the model and its sensitivity was tested for uncertain parameters by a Latin hypercube sensitivity design. For the latter each parameter tested was subject to a 20% coefficient of variation. The model parasitological outputs were most sensitive to the immune rate parameters that affected overall worm burdens. The model predicted the expected larger worm burdens along with disproportionately greater body weight losses with increasing daily infection levels. The model was validated against published literature using graphical and statistical comparisons. Its predictions were quantitatively consistent with the parasitological outputs of published experiments in which calves were subjected to different infection levels. The consequences of model weaknesses are discussed and point towards model improvements. Future work should focus on developing a stochastic model to account for calf variation in performance and immune response; this will ultimately be used to test the effectiveness of different parasite control strategies in naturally infected calf populations.

Modelling parasite transmission in a grazing system: the importance of host behaviour and immunity

Parasitic helminths present one of the most pervasive challenges to grazing herbivores. Many macro-parasite transmission models focus on host physiological defence strategies, omitting more complex interactions between hosts and their environments. This work represents the first model that integrates both the behavioural and physiological elements of gastro-intestinal nematode transmission dynamics in a managed grazing system. A spatially explicit, individual-based, stochastic model is developed, that incorporates both the hosts' immunological responses to parasitism, and key grazing behaviours including faecal avoidance. The results demonstrate that grazing behaviour affects both the timing and intensity of parasite outbreaks, through generating spatial heterogeneity in parasite risk and nutritional resources, and changing the timing of exposure to the parasites' free-living stages. The influence of grazing behaviour varies with the host-parasite combination, dependent on the development times of different parasite species and variations in host immune response. Our outputs include the counterintuitive finding that under certain conditions perceived parasite avoidance behaviours (faecal avoidance) can increase parasite risk, for certain host-parasite combinations. Through incorporating the two-way interaction between infection dynamics and grazing behaviour, the potential benefits of parasite-induced anorexia are also demonstrated. Hosts with phenotypic plasticity in grazing behaviour, that make grazing decisions dependent on current parasite burden, can reduce infection with minimal loss of intake over the grazing season. This paper explores how both host behaviours and immunity influence macro-parasite transmission in a spatially and temporally heterogeneous environment. The magnitude and timing of parasite outbreaks is influenced by host immunity and behaviour, and the interactions between them; the incorporation of both regulatory processes is required to fully understand transmission dynamics. Understanding of both physiological and behavioural defence strategies will aid the development of novel approaches for control.

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

Refugia-based treatment strategies aim to prolong anthelmintic efficacy by maintaining a parasite population unexposed to anthelmintics. Targeted selective treatment (TST) achieves this by treating only animals that will benefit most from treatment, using a determinant criterion (DC). We developed a mathematical model to compare various traits proposed as DC, and investigate impacts of TST and drenching frequency on sheep performance and anthelmintic resistance. Short term, decreasing the proportion of animals drenched reduced benefits of anthelmintic treatment, assessed by empty body weight (EBW), but decreased the rate of anthelmintic resistance development; each consecutive drenching had a reduced impact on average EBW and an increased impact on the rate of anthelmintic resistance emergences. The optimal DC was fecal egg count, maintaining the highest average EBW when reducing the proportion of animals drenched. Long-term, reducing the proportion of animals drenched had little impact on total weight gain benefits, across animals and years, whilst reducing drenching frequency increased it. Decreasing the frequency and proportion of animals drenched were both predicted to increase the duration of anthelmintic efficacy but reduce the total number of drenches administered before resistance was observed. TST and frequency of drenching may lead to different benefits in the short versus long term.

Livestock Helminths in a Changing Climate: Approaches and Restrictions to Meaningful Predictions

Climate change is a driving force for livestock parasite risk. This is especially true for helminths including the nematodes Haemonchus contortus, Teladorsagia circumcincta, Nematodirus battus, and the trematode Fasciola hepatica, since survival and development of free-living stages is chiefly affected by temperature and moisture. The paucity of long term predictions of helminth risk under climate change has driven us to explore optimal modelling approaches and identify current bottlenecks to generating meaningful predictions. We classify approaches as correlative or mechanistic, exploring their strengths and limitations. Climate is one aspect of a complex system and, at the farm level, husbandry has a dominant influence on helminth transmission. Continuing environmental change will necessitate the adoption of mitigation and adaptation strategies in husbandry. Long term predictive models need to have the architecture to incorporate these changes. Ultimately, an optimal modelling approach is likely to combine mechanistic processes and physiological thresholds with correlative bioclimatic modelling, incorporating changes in livestock husbandry and disease control. Irrespective of approach, the principal limitation to parasite predictions is the availability of active surveillance data and empirical data on physiological responses to climate variables. By combining improved empirical data and refined models with a broad view of the livestock system, robust projections of helminth risk can be developed.

In silico exploration of the mechanisms that underlie parasite-induced anorexia in sheep

A model was used to investigate two mechanisms describing reductions in food intake (anorexia) observed during gastrointestinal parasitism in lambs, and to explore relationships between anorexia and food composition. The mechanisms were either a reduction in intrinsic growth rate, leading to a consequent reduction in food intake (mechanism 1; M1), or a direct reduction in food intake (mechanism 2; M2). For both mechanisms, lambs growing from 2 to 6 months of age were modelled, with one of three levels of trickle challenge withTeladorsagia circumcincta. Scenarios were simulated for feeds varying in either protein or energy content, or both. Major differences were found between the predictions resulting from M1 and M2 on low-energy foods that constrained the intake of uninfected lambs through bulk. With M1, food intake was governed by the first operating constraint, whereas with M2 an additivity of constraints was observed. On the other foods, the duration of anorexia increased with increasing energy content of feed for M1, whilst the duration of anorexia decreased with increasing protein content of feed for M2.For foods that did not have an impact upon lambs' gastrointestinal tract capacity, published data were consistent with predictions of M2. Due to an absence of experimental data, no conclusions could be drawn for relationships between anorexia and food composition in the presence of other limiting constraints, such as bulk for low-energy foods. In conclusion, available experimental data and model predictions were consistent with anorexia having an impact directly on food intake, and with impacts of anorexia increasing with decreasing protein content.

The dynamic influence of genetic variation on the susceptibility of sheep to gastrointestinal nematode infection

The interaction between sheep and the nematode Teladorsagia circumcincta is one of the best understood of all host-parasite interactions. Following infection, there is considerable variation among lambs in the number of nematode eggs produced, the number of early fourth-stage larvae and the number of adult worms in the mucosa. These traits have a high variance to mean ratio (i.e. they are overdispersed or aggregated among hosts), they are skewed and approximately negative binomially distributed. The sources of overdispersion are differences among lambs in the ingestion of infective larvae and the immune response. Both forces can produce aggregation but their relative importance is unknown. The key components of variation can be identified by variance analysis. The sum of the average effects of polymorphic genes is known as additive genetic variation and this increases essentially from zero at one month of age to quite high values at six months of age. The major mechanism underlying genetic variation appears to be the differences among individuals in immune responses. Two of the major sources of variation in immune responses are differences in antigen recognition and differences in the type of cytokines produced. Genes that influence both these sources of variation are associated with differences in resistance to nematode infection. Therefore, much of the heterogeneity among animals in parasite transmission appears to be due to genetic variation in immune responsiveness.

A model to account for the consequences of host nutrition on the outcome of gastrointestinal parasitism in sheep: logic and concepts

A deterministic, dynamic simulation model is developed to account for the interactions between gastrointestinal parasitism and host nutrition, and predict their consequences on performance and level of parasitism of sheep. Larval intake and established adult worms are assumed to result in nutrient loss for the host. In order to reduce this loss the host will mount an immune response, which will affect the establishment rate of incoming larvae, mortality rate of adult worms, and fecundity of female worms, as well as nutrient loss caused by larval intakeper se. Host anorexia is modelled as a function of worm mass. Parasitism is also assumed to affect the allocation of ingested nutrients to the host's bodily functions, with maintenance getting absolute priority, and protein allocated to immunity and production proportionally to their requirements. Inputs to the model include the expected growth attributes of the animal, feed quality, various parasitological parameters and daily larval intake. Outputs include feed intake, growth rate and body composition, as well as worm burden and faecal egg counts. The model allows exploration of the consequences of gastrointestinal parasitism on sheep of different growth characteristics, kept under environments that vary in the provision of nutrients and exposure to parasites.

Gastrointestinal nematode parasites of sheep: a dynamic model for their effect on liveweight gain

This paper presents an individual-based model for gastrointestinal nematode parasites of sheep and includes the effect of these parasites on the liveweight performance of young sheep. Parasitism is known to affect the host animal in at least two ways. The first induces a loss of appetite in the host, which reduces pasture consumption compared with the parasite-free animal. This effect is examined in the first part of the study. The second major effect of parasitism is a reduction in the metabolic efficiency of the host which decreases nutrients available for maintenance and growth. The latter part of the paper examines the consequences of incorporating this effect on the liveweight changes in individuals in a group of sheep. Previous models addressing this issue have only given mean liveweight and worm burden changes.