Daily Variability of Strongyle Fecal Egg Counts in Horses

Parascaris spp. eggs shedding patterns in juvenile horses

Parascaris spp. infect foals worldwide and foals typically shed eggs in the feces from about three to six months of age, upon which natural immunity is incurred. High levels of anthelmintic resistance of Parascaris spp. are a global concern, and further understanding egg shedding patterns and fecal egg counting (FEC) data variability is of high importance. The aims of this study were to monitor Parascaris spp. egg shedding in untreated foals during 12-23 weeks of age, estimate sources of data variability, and assess precision of two ascarid FEC techniques. Fecal samples were collected weekly from 11 foals born in 2022, from May through November (29 weeks). Six subsamples were extracted from each weekly sample to determine 30 FECs between two techniques: a McMaster technique and an Automated Egg Counting System (AECS). Mixed linear modeling was carried out with age, sex, birth month, seasonality, spring- or summer-born foals, and egg counting technique as explanatory variables. Ascarid FECs were associated with age (p < 0.001), seasonality (p < 0.001), and technique (p < 0.001). The McMaster technique was more precise with a mean coefficient of variation (CV) of 34.57% and a 95% confidence interval (CI) of 30.80%- 38.30% compared to the CV for the AECS, which was 42.22% (CI: 37.70%-46.70%). Seasonality accounted for the highest proportion of variance (PV) of all covariates, but differences in PVs for covariates existed between techniques with foal age and subsample contributing more variance to the McMaster, and individual foal and seasonality contributing more to the AECS. Subsamples and replicate counts accounted for less than 1% of the total data variance. The results highlighted substantial differences in PVs between the two techniques at the subsample (AECS: 57.14%; McMaster: 77.51%) and replicate count levels (AECS: 42.86%; McMaster: 22.49%). While differences in precision were observed between the two FEC techniques, they were negligible in the data set, as the overwhelming majority of the data variability in ascarid FECs was attributed to individual foal, seasonality, and foal age.

Comparison of ovine faecal Strongyle egg counts from an accredited laboratory and a rapid, on-site parasite diagnostic system utilising a smartphone app and machine learning

Traditional treatment for gastrointestinal helminths in grazing livestock often involves untargeted, metaphylactic blanket treatment of animals with anthelmintics. As a result, resistance to anthelmintic drugs has become a significant issue for farmers and veterinarians worldwide, impacting farm profitability and animal welfare. Faecal egg counts (FECs) are an important diagnostic test to combat further anthelmintic resistance as they enable practitioners to better distinguish between animals that require treatment and those that do not. FECs are labour-intensive, time-consuming and require trained personnel to process the samples and visually identify the parasite eggs. Consequently, the time between sample collection, transport, analysis, results, and treatment can take days. This study aimed to evaluate a rapid, on-site parasite diagnostic system utilising a smartphone app and machine learning in terms of its capability to provide reliable egg counts while decreasing the turnaround time for results associated with outsourcing the analysis. A total of 105 ovine faecal samples were collected. Each sample was homogenised and split equally between two containers. One container per sample was processed using the on-site, app-based system, the second container was sent to an accredited laboratory. Strongyle egg counts were conducted via video footage of samples by the system's machine learning (ML) and a trained technician (MT) and via microscopic examination by an independent laboratory technician (LAB). Results were statistically analysed using a generalised linear model using SAS® (Version 9.4) software. The ratio of means was used to determine non-inferiority of the ML results compared to the LAB results. Both system egg counts (ML and MT) were higher (p < 0.0001) compared to those obtained from the laboratory (LAB). There was no statistically significant difference between the ML and MT counts. The app-based system utilising machine learning has been found to be non-inferior to the accredited laboratory at quantifying Strongyle eggs in ovine faecal samples. With its quick result turnaround, low outlay cost and reusable components, this portable diagnostic system can help veterinarians to increase their testing capacity, perform on-farm testing and deliver faster and more targeted parasite treatment to combat anthelmintic resistance.

World Association for the Advancement of Veterinary Parasitology (W.A.A.V.P.) guideline for diagnosing anthelmintic resistance using the faecal egg count reduction test in ruminants, horses and swine

The faecal egg count reduction test (FECRT) remains the method of choice for establishing the efficacy of anthelmintic compounds in the field, including the diagnosis of anthelmintic resistance. We present a guideline for improving the standardization and performance of the FECRT that has four sections. In the first section, we address the major issues relevant to experimental design, choice of faecal egg count (FEC) method, statistical analysis, and interpretation of the FECRT results. In the second section, we make a series of general recommendations that are applicable across all animals addressed in this guideline. In the third section, we provide separate guidance details for cattle, small ruminants (sheep and goats), horses and pigs to address the issues that are specific to the different animal types. Finally, we provide overviews of the specific details required to conduct an FECRT for each of the different host species. To address the issues of statistical power vs. practicality, we also provide two separate options for each animal species; (i) a version designed to detect small changes in efficacy that is intended for use in scientific studies, and (ii) a less resource-intensive version intended for routine use by veterinarians and livestock owners to detect larger changes in efficacy. Compared to the previous FECRT recommendations, four important differences are noted. First, it is now generally recommended to perform the FECRT based on pre- and post-treatment FEC of the same animals (paired study design), rather than on post-treatment FEC of both treated and untreated (control) animals (unpaired study design). Second, instead of requiring a minimum mean FEC (expressed in eggs per gram (EPG)) of the group to be tested, the new requirement is for a minimum total number of eggs to be counted under the microscope (cumulative number of eggs counted before the application of a conversion factor). Third, we provide flexibility in the required size of the treatment group by presenting three separate options that depend on the (expected) number of eggs counted. Finally, these guidelines address all major livestock species, and the thresholds for defining reduced efficacy are adapted and aligned to host species, anthelmintic drug and parasite species. In conclusion, these new guidelines provide improved methodology and standardization of the FECRT for all major livestock species.

A statistical framework for calculating prospective sample sizes and classifying efficacy results for faecal egg count reduction tests in ruminants, horses and swine

The faecal egg count reduction test (FECRT) is the primary diagnostic tool used for detecting anthelmintic resistance at the farm level. It is therefore extremely important that the experimental design of a FECRT and the susceptibility classification of the result use standardised and statistically rigorous methods. Several different approaches for improving the analysis of FECRT data have been proposed, but little work has been published on how to address the issue of prospective sample size calculations. Here, we provide a complete and detailed overview of the quantitative issues relevant to a FECRT starting from basic statistical principles. We then present a new approach for determining sample size requirements for the FECRT that is built on a solid statistical framework, and provide a rigorous anthelminthic drug efficacy classification system for use with FECRT in livestock. Our approach uses two separate statistical tests, a one-sided inferiority test for resistance and a one-sided non-inferiority test for susceptibility, and determines a classification of resistant, susceptible or inconclusive based on the combined result. Since this approach is based on two independent one-sided tests, we recommend that a 90 % CI be used in place of the historically used 95 % CI. This maintains the desired Type I error rate of 5 %, and simultaneously reduces the required sample size. We demonstrate the use of this framework to provide sample size calculations that are rooted in the well-understood concept of statistical power. Tailoring to specific host/parasite systems is possible using typical values for expected pre-treatment and post-treatment variability in egg counts as well as within-animal correlation in egg counts. We provide estimates for these parameters for ruminants, horses and swine based on a re-examination of datasets that were available to us from a combination of published data and other sources. An illustrative example is provided to demonstrate the use of the framework, and parameter estimates are presented to estimate the required sample size for a hypothetical FECRT using ivermectin in cattle. The sample size calculation method and classification framework presented here underpin the sample size recommendations provided in the upcoming FECRT WAAVP guidelines for detection of anthelmintic resistance in ruminants, horses, and swine, and have also been made freely available as open-source software via our website (https://www.fecrt.com).

Effects of sample homogenizing on the performance of an automated strongylid egg counting system

Fecal egg counts are essential monitoring tools in veterinary parasite control. In recent years, several groups have developed automated egg counting systems based on image analysis and deep learning algorithms. Work in our laboratory demonstrated that an automated system performed with significantly better precision than traditional egg counting techniques. However, while the counting process is no longer operator dependent, the pre-analytical homogenization steps still are. This study aimed at evaluating the influence of sample homogenization on diagnostic performance on an automated equine strongylid egg counting system. Samples were collected from 12 horses and assigned to three egg count categories (four samples per category): Low (0-500 eggs per gram (EPG)), Moderate (501-1000 EPG), and High (1001-2000 EPG). Within each category, all samples were divided into four portions and each was analyzed with the automated system using the following four homogenizing procedures using a homogenizing device supplied with the system: 1) pressing the plunger five times and pouring directly into the counting chamber, 2) pressing the plunger five times and shaking the bottle prior to pouring, 3) pressing the plunger ten times with direct pouring, and 4) pressing the plunger ten times with shaking the bottle before pouring. There were no differences in precision expressed as coefficient of variation between these four procedures but shaking of the bottle prior to pouring was significantly associated with higher counts (p = 0.0068). These results demonstrate that the homogenization process can affect the diagnostic performance of an automated egg counting system and suggest that more efforts should be invested in standardizing and optimizing homogenization procedures.

Comparative studies on faecal egg counting techniques used for the detection of gastrointestinal parasites of equines: A systematic review

Faecal egg counting techniques (FECT) form the cornerstone for the detection of gastrointestinal parasites in equines. For this purpose, several flotation, centrifugation, image- and artificial intelligence-based techniques are used, with varying levels of performance. This review aimed to critically appraise the literature on the assessment and comparison of various coprological techniques and/or modifications of these techniques used for equines and to identify the knowledge gaps and future research directions. We searched three databases for published scientific studies on the assessment and comparison of FECT in equines and included 27 studies in the final synthesis. Overall, the performance parameters of McMaster (81.5%), Mini-FLOTAC® (33.3%) and simple flotation (25.5%) techniques were assessed in most of the studies, with 77.8% of them comparing the performance of at least two or three methods. The detection of strongyle, Parascaris spp. and cestode eggs was assessed for various FECT in 70.4%, 18.5% and 18.5% studies, respectively. A sugar-based flotation solution with a specific gravity of ≥1.2 was found to be the optimal flotation solution for parasitic eggs in the majority of FECT. No uniform or standardised protocol was followed for the comparison of various FECT, and the tested sample size (i.e. equine population and faecal samples) also varied substantially across all studies. To the best of our knowledge, this is the first systematic review to evaluate studies on the comparison of FECT in equines and it highlights important knowledge gaps in the evaluation and comparison of such techniques.

Intestinal parasites in Przewalski's horses (Equus ferus przewalskii): a field survey at the Hortobágy National Park, Hungary

The Pentezug Wildhorse Reserve, located in the Hortobágy National Park, Hungary, has one of the biggest ex situ populations of Przewalski's horses and aims to preserve its landscape and to study this subspecies. Between September and November 2018, 79 faecal samples were collected from Przewalski's horses. The McMaster, Willis flotation, natural sedimentation and coproculture methods were applied to all the samples. Results showed an average level of 1287 eggs per gram (EPG), which is a high faecal egg-shedding level. All the samples were positive for strongyle-type eggs (100%). There were no statistical differences regarding the EPG values between different harems of the population. The same happened when considering sexes, ages, lactating status or when bachelors are compared with harem members. Cyathostominae were dominant, when compared to Strongylinae and Tricostrongylidae, and 15 different morphological infective third-stage larvae types and/or species belonging to the order Strongylida were identified. The subfamily Cyathostominae was prevalent in 100% of the horses. Strongylus vulgaris was the most prevalent strongylin (40.5%). Additionally, 27.8% were positive for Parascaris sp. and 2.5% showed Oxyuris equi in their faeces. This study revealed that there is a higher prevalence of Triodontophorus serratus and Poteriostomum spp. in juveniles. Horses with S. vulgaris showed lower levels of EPG. This was the first study involving this population, showing 100% prevalence of intestinal parasites.

What makes a good fecal egg count technique?

The first parasite fecal egg counting techniques were described over 100 years ago, and fecal egg counting remains essential in parasitology research as well as in clinical practice today. Several novel techniques have been introduced and validated in recent years, but this work has also highlighted several current issues in this research field. There is a lack of consensus on which diagnostic parameters to evaluate and how to properly design studies doing so. Furthermore, there is a confusing and sometimes incorrect use of terminology describing performance of fecal egg counting techniques, and it would be helpful to address these. This manuscript reviews qualitative and quantitative diagnostic performance parameters, discusses their relevance for fecal egg counting techniques, and highlights some of the challenges with determining them. Qualitative parameters such as diagnostic sensitivity and specificity may be considered classic diagnostic performance metrics, but they generally only have implications at low egg count levels. The detection limit of a given technique is often referred to as the "analytical sensitivity", but this is misleading as the detection limit is a theoretically derived number, whereas analytical sensitivity is determined experimentally. Thus, the detection limit is not a diagnostic performance parameter and does not inform on the diagnostic sensitivity of a technique. Quantitative performance parameters such as accuracy and precision are highly relevant for describing the performance of fecal egg counting techniques, and precision is arguably the more important of the two. An absolute determination of accuracy can only be achieved by use of samples spiked with known quantities of parasite ova, but spiking does not necessarily mimic the true distribution of eggs within a sample, and accuracy estimates are difficult to reproduce between laboratories. Instead, analysis of samples from naturally infected animals can be used to achieve a relative ranking of techniques according to egg count magnitude. Precision can be estimated in a number of different approaches, but it is important to ensure a relevant representation of egg count levels in the study sample set, as low egg counts tend to associate with lower precision estimates. Coefficients of variation generally provide meaningful measures of precision that are independent of the multiplication factor of the techniques evaluated. Taken together, there is a need for clear guidelines for studies validating fecal egg counting techniques in veterinary parasitology with emphasis on what should be evaluated, how studies could be designed, and how to appropriately analyze the data. Furthermore, there is a clear need for better consensus regarding use of terminology describing the diagnostic performance of fecal egg count techniques.

The effect of analyst training on fecal egg counting variability

Fecal egg counts (FECs) are essential for veterinary parasite control programs. Recent advances led to the creation of an automated FEC system that performs with increased precision and reduces the need for training of analysts. However, the variability contributed by analysts has not been quantified for FEC methods, nor has the impact of training on analyst performance been quantified. In this study, three untrained analysts performed FECs on the same slides using the modified McMaster (MM), modified Wisconsin (MW), and the automated system with two different algorithms: particle shape analysis (PSA) and machine learning (ML). Samples were screened and separated into negative (no strongylid eggs seen), 1-200 eggs per gram of feces (EPG), 201-500 EPG, 501-1000 EPG, and 1001+ EPG levels, and ten repeated counts were performed for each level and method. Analysts were then formally trained and repeated the study protocol. Between analyst variability (BV), analyst precision (AP), and the proportion of variance contributed by analysts were calculated. Total BV was significantly lower for MM post-training (p = 0.0105). Additionally, AP variability and analyst variance both tended to decrease for the manual MM and MW methods. Overall, MM had the lowest BV both pre- and post-training, although PSA and ML were minimally affected by analyst training. This research illustrates not only how the automated methods could be useful when formal training is unavailable but also how impactful formal training is for traditional manual FEC methods.

Diagnostic performance of McMaster, Wisconsin, and automated egg counting techniques for enumeration of equine strongyle eggs in fecal samples

Fecal egg counts are the cornerstone of equine parasite control programs. Previous work led to the development of an automated, image-analysis-based parasite egg counting system. The system has been further developed to include an automated reagent dispenser unit and a custom camera (CC) unit that generates higher resolution images, as well as a particle shape analysis (PSA) algorithm and machine learning (ML) algorithm. The first aim of this study was to conduct a comprehensive comparison of method precision between the original smartphone (SP) unit with the PSA algorithm, CC/PSA, CC/ML, and the traditional McMaster (MM) and Wisconsin (MW) manual techniques. Additionally, a Bayesian analysis was performed to estimate and compare sensitivity and specificity of all five methods. Feces were collected from horses, screened with triplicate Mini-FLOTAC counts, and placed into five categories: negative (no eggs seen), > 0 - ≤ 200 eggs per gram (EPG), > 200 - ≤ 500 EPG, > 500 - ≤ 1000 EPG, and > 1000 EPG. Ten replicates per horse were analyzed for each technique. Technical variability for samples > 200 EPG was significantly higher for MM than CC/PSA and CC/ML (p <  0.0001). Biological variability for samples> 0 was numerically highest for CC/PSA, but with samples > 200 EPG, MM had a significantly lower CV than MW (p =  0.001), MW had a significantly lower CV than CC/PSA (p <  0.0001), CC/ML had a significantly lower CV than both MW and SP/PSA (p <  0.0001, p =  0.0003), and CC/PSA had a significantly lower CV than CC/SP (p =  0.0115). Sensitivity was> 98 % for all five methods with no significant differences. Specificity, however, was significantly the highest for CC/PSA, followed numerically by SP/PSA, MM, CC/ML, and finally MW. Overall, the automated counting system is a promising new development in equine parasitology. Continued refinement to the counting algorithms will help improve precision and specificity, while additional research in areas such as egg loss, analyst variability at the counting step, and accuracy will help create a complete picture of its impact as a new fecal egg count method.

The non-invasive measurement of faecal immunoglobulin in African equids

Eco-immunological research is encumbered by a lack of basic research in a wild context and by the availability of few non-invasive tools to measure the internal state of wild animals. The recent development of an enzyme-linked immunosorbent assay for measuring immunoglobulins in faecal samples from Soay sheep prompted us to optimize such an assay to measure immunoglobulin A (IgA: an antibody associated with parasitic nematode fecundity) in faecal samples from equids. We measured total IgA in domestic donkeys, wild plains zebras, and wild Grevy's zebras sharing the same landscape in central Kenya over two field seasons. Attempts to measure anti-nematode IgA more specifically, using a homogenized extract from a mixture of excreted nematodes, failed to clear background. However, we found that total IgA positively correlated with strongyle nematode faecal egg counts (FECs) in donkeys sampled during the wetter field season - a time when the donkeys were in good condition. Further, this relationship appeared among donkeys with high body condition but not among those with low body condition. Time lags of 1–4 days introduced between IgA and FEC measurements in repeatedly sampled donkeys did not yield correlations, suggesting that IgA and FEC roughly tracked one another without much delay in the wet field season. Such a direct IgA-FEC relationship did not appear for zebras in either the wet or dry field season, possibly due to higher interindividual variation in body condition among the free-roaming zebras than in the donkeys. However, Grevy's zebras had higher overall levels of IgA than either plains zebras or donkeys, potentially associated with their reportedly lower FECs at the population level. Our results suggest that equids may mount an IgA response to nematode egg production when the host is in good condition and that equid species may differ in baseline levels of mucosal IgA.

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We optimized an immunosorbent assay to non-invasively measure total IgA in faeces from equids.

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IgA positively correlated with nematode faecal egg count (FEC) in donkeys in good body condition.

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IgA and FEC were not correlated in a dry year for donkeys or in any year for wild plains and Grevy's zebras.

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IgA may relate to FECs at the population level only when body condition is uniformly good.

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IgA was higher in Grevy's than plains zebras or donkeys, suggesting differences in immune strategy.

The effect of counting duration on quantitative fecal egg count test performance

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Rapid counting reduces McMaster accuracy by 50–60% and precision by one third.

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Counting only one McMaster grid does not affect accuracy but decreases precision by one third.

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Automated counting operates with equal accuracy to McMaster but twice the precision.

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Strongylid ova suspended in sodium nitrate become translucent over time.

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Increased translucency is associated with a 5% underestimation of egg counts.

Fecal egg counts are the primary diagnostic tools of equine parasitology and use of the McMaster test and its variants in clinical practice is widely recommended. Manual counting is, however, prone to various sources of human error. For example, in real-world situations analysts can be under significant pressure to process high numbers of samples in a limited time. This practice could affect test result quality, but yet no studies have determined whether this is the case. This study’s purpose was to assess the effect of shortened counting duration (from either restricting counting time or counting only one grid of a slide) on McMaster test performance, and to compare the results to those of an automated test whose output is not subject to such limitations. Fifteen fecal samples from horses infected with strongylid parasites were divided equally into three groups based on high, medium and low levels of egg content (201–500, 501–1000 and 1001+ eggs/g). Slurries were produced from each sample and 10 subsamples of each were counted by both the McMaster and automated methods. McMaster slides were first counted at leisure, and then twice again with counting time being restricted to either one or two min. The effect of reducing sample processing time by counting only one grid of the McMaster slide was also assessed. Counting for one min significantly decreased manual egg counts by 50–60% relative to counts conducted at leisure (p < 0.001). While these decreases were somewhat ameliorated by counting for two min, the results were still approximately 10% lower than the at-leisure counts, a difference that was also statistically significant (p < 0.001). Furthermore, restricted counting duration also resulted in a significant decrease of approximately one-third in McMaster test precision, as assessed by the coefficients of variation (CoVs) of the 10 replicates of each sample, as did counting just a single grid of the McMaster slide. These differences effectively further improved the observed superior precision of the automated method compared to at-leisure manual McMaster counting, and the automated counts and their precision remained relatively unaffected following multiple analyses of the same processed samples. Taken together, these results indicate that analysists should carefully assess the possible effects on test performance of modifications to standard egg-counting procedures that are designed to account for real-world pressures, in order to achieve an optimal compromise between test accuracy and precision on one hand and practicality on the other.

The application of faecal egg count results and statistical inference for clinical decision making in foals

This study investigated the impact of variability in Parascaris spp. and strongyle faecal egg counts (FEC) from foals on treatment decision-making and detection of a patent infection. A single faecal sample was collected once daily for three days from 53 foals and a FEC was performed on three separate portions of each sample (total of nine egg counts per foal). Differences in the decision to administer an anthelmintic using the results of a single count (C₁), the mean of three (X¯_1-3) or nine counts (X¯_1-9) and the upper 5% confidence limit of the gamma confidence interval (CI) of the estimate of the distribution mean (μ) from three (UCL_1-3) and nine counts (UCL_1-9) were determined for a range of egg count thresholds. The UCL_1-9 was used as the best estimate of μ, hypothesis testing for treatment and the comparison of treatment decision-making using C₁, X¯_1-3, X¯_1-9 and UCL_1-3. The results of this study demonstrated that a point estimate (C₁ or X¯_1-3) was of limited value for estimating the distribution mean of egg counts in faeces and there was overall poor agreement in treatment decision-making for individual foals using C₁ compared with UCL_1-9. Of the foals with C₁ of zero eggs per gram, 54% and 47% had Parascaris and strongyle eggs in subsequent counts, respectively. The egg density in faeces is inhomogeneous, resulting in considerable variability in egg count results for an individual foal: between faecal piles, different portions of a faecal pile and days. The use of the negative binomial distribution CI for μ takes this variability into account and is recommended for use when interpreting FEC data from horses.

Anthelmintic efficacy of single active and combination products against commonly occurring parasites in foals

Parasite control in foals is complicated by the concurrent presence of biologically diverse parasites with differing levels of anthelmintic resistance. Several combination anthelmintic products are available for use in horses, but information on their efficacies against important equine parasites is scarce. Two trials were performed in New Zealand during 2008 and 2011 on four different farms with substantially different anthelmintic treatment histories. The first trial evaluated the efficacy of an ivermectin/praziquantel/oxibendazole combination, a single active oxibendazole, and a single-active macrocyclic lactone (ML) in 49 foals located on three farms. The second trial evaluated two combination anthelmintic products and three single-active ML products and enrolled a total of 110 foals on three farms. Foals in the second trial were allocated to one of six anthelmintic treatment groups; oxfendazole/pyrantel embonate, pyrantel embonate/ivermectin/praziquantel, ivermectin/praziquantel, abamectin/praziquantel, moxidectin/praziquantel, and a placebo-treated control. In both trials, foals were monitored monthly prior to treatment, and fecal egg counts (FECs) of Parascaris spp., strongylid, and Strongyloides westeri were determined. A "rolling enrolment" process was implemented whereby foals were systematically allocated to a treatment group and treated with the corresponding anthelmintic following the first appearance of Parascaris spp. eggs in the faeces. A generalised linear model was used to evaluate the effect of farm and treatment on Day14 FEC (ln) for each parasite. Three different FECR calculation methods were employed as follows; i) FECR(T) pre and post treatment ii) FECR (C) in the treated group compared with control, and iii) FECR (P) pre- and post- treatment in the treated and control groups. Across both trials, treatment with ML single active products failed to achieve >95% reduction in Parascaris spp. FEC on two of three farms. The pyrantel embonate/oxfendazole and ivermectin/ praziquantel/oxibendazole combinations demonstrated full efficacy against Parascaris spp. This is in contrast to the anti-strongylid efficacies determined, where the pyrantel embonate/oxfendazole combination and single active oxibendazole had reduced efficacy on one farm, while the macrocyclic lactones generally had good efficacy. Strongyloides egg counts were sporadic in both trials, and allowed limited insight into anthelmintic efficacy. The study illustrated the importance of keeping an untreated or placebo-treated control group in studies evaluating anti-Parascaris efficacy and it demonstrated the utility of a rolling enrolment procedure, where foals are enrolled over the course of a defined period of time. Furthermore, the study demonstrated the value of a farm specific FECR monitoring programme and the complexity of parasite control in foals, where combination anthelmintic products can be employed to target multiple species of parasites.

Gastro-intestinal parasite infections of Ankole cattle in an unhealthy landscape: An assessment of ecological predictors

The distribution of gastro-intestinal (GI) parasites across landscapes is closely related to the spatial distribution of hosts. In GI parasites with environmental life stages, the vitality of parasites is also affected by ecological and landscape-related components of the environment. This is particularly relevant for domestic livestock species that are often kept across habitats with varying degrees of degradation, exposing them to a wide range of environmentally robust parasite species. In our study, we examined the effect of environmental and anthropogenic factors on the prevalence and intensity of GI parasites across a free-ranging stock of Ankole cattle in the Mutara rangelands of northeastern Rwanda. Prevalence and intensity of each parasite type (i.e., strongyle-type nematodes, Strongyloides spp., Moniezia spp., and Eimeria spp.) were used as dependent variables. Two fixed factors related to season and conservation-political history, together with three principal components (condensed from nine ecological variables) were used as independent covariates in a univariate General Linear Model (GLM). Major effects on the prevalence and intensity of strongyle-type nematodes and on the intensity of Eimeria spp. were found in that vegetation-related effects such as above-ground grass biomass in conjunction with a high degree of soil compaction had a negative relationship with these parasite types. These unexpected findings suggest that strongyle-type and coccidian infections increase with increasing rangeland degradation. Strongyle-type nematode prevalence and intensity were also negatively related to goat/sheep density, indicating a 'dilution effect' of GI infections between domestic livestock species.

Evaluation of accuracy and precision of a smartphone based automated parasite egg counting system in comparison to the McMaster and Mini-FLOTAC methods

Fecal egg counts are emphasized for guiding equine helminth parasite control regimens due to the rise of anthelmintic resistance. This, however, poses further challenges, since egg counting results are prone to issues such as operator dependency, method variability, equipment requirements, and time commitment. The use of image analysis software for performing fecal egg counts is promoted in recent studies to reduce the operator dependency associated with manual counts. In an attempt to remove operator dependency associated with current methods, we developed a diagnostic system that utilizes a smartphone and employs image analysis to generate automated egg counts. The aims of this study were (1) to determine precision of the first smartphone prototype, the modified McMaster and ImageJ; (2) to determine precision, accuracy, sensitivity, and specificity of the second smartphone prototype, the modified McMaster, and Mini-FLOTAC techniques. Repeated counts on fecal samples naturally infected with equine strongyle eggs were performed using each technique to evaluate precision. Triplicate counts on 36 egg count negative samples and 36 samples spiked with strongyle eggs at 5, 50, 500, and 1000 eggs per gram were performed using a second smartphone system prototype, Mini-FLOTAC, and McMaster to determine technique accuracy. Precision across the techniques was evaluated using the coefficient of variation. In regards to the first aim of the study, the McMaster technique performed with significantly less variance than the first smartphone prototype and ImageJ (p<0.0001). The smartphone and ImageJ performed with equal variance. In regards to the second aim of the study, the second smartphone system prototype had significantly better precision than the McMaster (p<0.0001) and Mini-FLOTAC (p<0.0001) methods, and the Mini-FLOTAC was significantly more precise than the McMaster (p=0.0228). Mean accuracies for the Mini-FLOTAC, McMaster, and smartphone system were 64.51%, 21.67%, and 32.53%, respectively. The Mini-FLOTAC was significantly more accurate than the McMaster (p<0.0001) and the smartphone system (p<0.0001), while the smartphone and McMaster counts did not have statistically different accuracies. Overall, the smartphone system compared favorably to manual methods with regards to precision, and reasonably with regards to accuracy. With further refinement, this system could become useful in veterinary practice.

Repeatability of strongyle egg counts in naturally infected horses

The selective treatment of horses is used to decrease the number of anthelmintic treatments by only treating a proportion of animals in the population. One way to select animals for treatment is to identify low and high egg-shedders using faecal egg counts (FEC); then to treat only the high egg-shedders. The value of this method is enhanced if differences among individuals in the level of egg-shedding remain consistent over time. One way to assess the stability of the rankings of animals over time is to measure the repeatability which is defined as the variance between horses divided by the total variance. The repeatability varies between 0 (no consistency in the values) to 1 (perfect consistency). To determine the repeatability of egg-shedding in naturally infected horses over time, 2637 FEC and raw egg counts (REC; i.e. originally counted eggs without multiplication factor) from 303 horses were analysed. The distribution of FEC was more overdispersed than a Poisson distribution. Therefore, a negative-binomial model was used. The within-horse-repeatability of RECs was 0.52. In a second analysis, we excluded horses that were treated with anthelmintic drugs during the study by eliminating all REC within the egg-reappearance-period. Here, the within-horse-repeatability was very similar at 0.53. The results show that egg-shedding of individual horses stays fairly consistent over time. They also show that animals which shed relatively high numbers of nematode eggs can be identified and targeted for treatment.

Negative covariance between parasite load and body condition in a population of feral horses

In wild and domestic animals, gastrointestinal parasites can have significant impacts on host development, condition, health, reproduction and longevity. Improving our understanding of the causes and consequences of individual-level variation in parasite load is therefore of prime interest. Here we investigated the relationship between strongyle fecal egg count (FEC) and body condition in a unique, naturalized population of horses that has never been exposed to anthelmintic drugs (Sable Island, Nova Scotia, Canada). We first quantified variation in FEC and condition for 447 individuals according to intrinsic (sex, age, reproductive status, social status) and extrinsic (group size, location, local density) variables. We then quantified the repeatability of measurements obtained over a field season and tested for covariance between FEC and condition. FECs were high relative to other horse populations (mean eggs per gram ± SD = 1543·28 ± 209·94). FECs generally decreased with age, were higher in lactatingvsnon-lactating females, and unexpectedly lower in males in some part of the island. FECs and condition were both spatially structured, with patterns depending on age, sex and reproductive status. FECs and condition were both repeatable. Most notably, FECs and condition were negatively correlated, especially in adult females.

A standardised faecal collection protocol for intestinal helminth egg counts in Asian elephants, Elephas maximus

The quantitative assessment of parasite infection is necessary to measure, manage and reduce infection risk in both wild and captive animal populations. Traditional faecal flotation methods which aim to quantify parasite burden, such as the McMaster egg counting technique, are widely used in veterinary medicine, agricultural management and wildlife parasitology. Although many modifications to the McMaster method exist, few account for systematic variation in parasite egg output which may lead to inaccurate estimations of infection intensity through faecal egg counts (FEC). To adapt the McMaster method for use in sampling Asian elephants (Elephas maximus), we tested a number of possible sources of error regarding faecal sampling, focussing on helminth eggs and using a population of over 120 semi-captive elephants distributed across northern Myanmar. These included time of day of defecation, effects of storage in 10% formalin and 10% formol saline and variation in egg distribution between and within faecal boluses. We found no significant difference in the distribution of helminth eggs within faecal matter or for different defecation times, however, storage in formol saline and formalin significantly decreased egg recovery. This is the first study to analyse several collection and storage aspects of a widely-used traditional parasitology method for helminth parasites of E. maximus using known host individuals. We suggest that for the modified McMaster technique, a minimum of one fresh sample per elephant collected from any freshly produced bolus in the total faecal matter and at any point within a 7.5 h time period (7.30am-2.55 pm) will consistently represent parasite load. This study defines a protocol which may be used to test pre-analytic factors and effectively determine infection load in species which produce large quantities of vegetative faeces, such as non-ruminant megaherbivores.