The effect of analyst training on fecal egg counting variability

Cain, Jennifer L.; Peters, Kerri T.; Suri, Parul; Roher, Amber; Rutledge, Matthew H.; Nielsen, Martin K.

doi:10.1007/s00436-021-07074-2

Cited by 18 publications

(12 citation statements)

References 20 publications

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“…In two out of three cases where data were available, the model overestimated the magnitude of the observations considerably, although in all cases the predicted time trend seems consistent with that of the data. There are, however, many factors, some of which method-related, that can limit the efficacy and cause variability in the field recovery of L3 (Cain et al, 2021; Kloosterman, 1971; Paras et al, 2018; Tontini et al, 2019; Verschave et al, 2015). In particular, the fact one or two of the L3 counts suddenly dropped to zero and then rebounded during the season (Fig.…”

Section: Resultsmentioning

confidence: 99%

“…However, many factors can contribute to low efficiency and sampling variation in the field recovery of L3. These factors include the recovery method and the analyst (Cain et al, 2021; Kloosterman, 1971; Paras et al, 2018; Verschave et al, 2015), differing grass growth and under-sampling of the sward at the lowest level (Tontini et al, 2019), soil-herbage migration of L3, and avoidance of faecal pats or dung beetles, which associate with higher L3 concentration (Henriksen et al, 1976; Nansen et al, 1988). Measurement variation within a study can result from limited sampling of highly aggregated L3, and this possibility cannot be excluded in the studies where L3 counts dropped to zero and rebounded during the season.…”

Section: Discussionmentioning

confidence: 99%

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

Filipe

Kyriazakis

McFarland

et al. 2022

Preprint

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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 forOstertagia 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 byO. ostertagiandCooperia 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 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.HIGHLIGHTSNematode control in cattle is complicated by drug resistance and climate changeA model was developed to predict GIN epidemiology under varying conditionsThe model incorporates cattle growth, infection and immunity, grass availability, weatherPredictions were validated against empirical studies of GIN in N EuropeThe model applies toOstertagia ostertagi, and possibly to co-infectingCooperiaAbstract Figurehttps://www.lmcni.com/

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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

Filipe

Kyriazakis

McFarland

et al. 2022

Preprint

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“…However, such a conclusion is clearly premature since it is based on data obtained by a single researcher (HB), who performed all of the the analyses. The finding may well be different if data from different researchers/technicians were to be included in the analysis, since higher variability in semi-quantitative methods is to be expected, particularly if samples are analysed by people with differing experience [ 56 ]. Standard operating procedures for semi-quantitative approaches are necessarily less precise than those for quantitative approaches.…”

Section: Discussionmentioning

confidence: 99%

Comparison of FECPAKG2, a modified Mini-FLOTAC technique and combined sedimentation and flotation for the coproscopic examination of helminth eggs in horses

et al. 2022

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Background Due to high prevalence of anthelmintic resistance in equine helminths, selective treatment is increasingly promoted and in some countries a positive infection diagnosis is mandatory before treatment. Selective treatment is typically recommended when the number of worm eggs per gram faeces (epg) exceeds a particular threshold. In the present study we compared the semi-quantitative sedimentation/flotation method with the quantitative methods Mini-FLOTAC and FECPAKG2 in terms of precision, sensitivity, inter-rater reliability and correlation of worm egg counts to improve the choice of optimal diagnostic tools. Methods Using sedimentation/flotation (counting raw egg numbers up to 200), we investigated 1067 horse faecal samples using a modified Mini-FLOTAC approach (multiplication factor of 5 to calculate epgs from raw egg counts) and FECPAKG2 (multiplication factor of 45). Results Five independent analyses of the same faecal sample with all three methods revealed that variance was highest for the sedimentation/flotation method while there were no significant differences between methods regarding the coefficient of variance. Sedimentation/flotation detected the highest number of samples positive for strongyle and Parascaris spp. eggs, followed by Mini-FLOTAC and FECPAKG2. Regarding Anoplocephalidae, no significant difference in frequency of positive samples was observed between Mini-FLOTAC and sedimentation/flotation. Cohen’s κ values comparing individual methods with the combined result of all three methods revealed almost perfect agreement (κ ≥ 0.94) for sedimentation/flotation and strong agreement for Mini-FLOTAC (κ ≥ 0.83) for strongyles and Parascaris spp. For FECPAKG2, moderate and weak agreements were found for the detection of strongyle (κ = 0.62) and Parascaris (κ = 0.51) eggs, respectively. Despite higher sensitivity, the Mini-FLOTAC mean epg was significantly lower than that with FECPAKG2 due to samples with > 200 raw egg counts by sedimentation/flotation, while in samples with lower egg shedding epgs were higher with Mini-FLOTAC than with FECPAKG2. Conclusions For the simple detection of parasite eggs, for example, to treat foals infected with Parascaris spp., sedimentation/flotation is sufficient and more sensitive than the other two quantitative investigared in this study. Mini-FLOTAC is predicted to deliver more precise results in faecal egg count reduction tests due to higher raw egg counts. Finally, to identify animals with a strongyle epg above a certain threshold for treatment, FECPAKG2 delivered results comparable to Mini-FLOTAC. Grpahical Abstract

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“…More recently, computerised image analysis technologies have been developed for automated faecal egg counting and systems now exist for cattle (Elghryani et al., 2020), small animals (Nagamori et al., 2020) and horses (Slusarewicz et al., 2016). These systems have the advantage of their performance being independent of operator training and skill and have been shown to perform with significantly better precision (Cain et al., 2021). Furthermore, processing time is significantly reduced in comparison with manual techniques without compromising diagnostic quality (Slusarewicz et al., 2019).…”

Section: Methodology Principlesmentioning

confidence: 99%

“…We recently evaluated the performance of four different faecal egg counting techniques in the hands of three untrained and inexperienced analysts. We had them complete the same study protocol both before and after formal laboratory training, and we demonstrated that precision improved significantly after the training (Cain et al., 2021). We also found that the Wisconsin technique performed with the lowest accuracy, but that this also improved after the training (Cain et al., 2021).…”

Section: Accuracy and Precisionmentioning

confidence: 96%

Parasite faecal egg counts in equine veterinary practice

Nielsen

2021

Equine Veterinary Education

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Summary Widespread occurrence of anthelmintic resistance in ascarid and strongylid parasites has led to recommendations of routine treatment efficacy screening with the faecal egg count reduction test. Furthermore, faecal egg counts are used for classifying mature horses into low, moderate and high strongylid egg shedders, and to monitor for ascarids in foals, weanlings and yearlings. The plethora of egg counting techniques is surrounded by confusion and misconception regarding their use, diagnostic performance and interpretation. This article aims to explain general concepts of evaluating and assessing faecal egg count test performance and address some of the most common misconceptions. The multiplication factor, which is used to convert the number of eggs counted under the microscope to eggs per gram of faeces, is a theoretically derived number, which does not reflect sensitivity. Accuracy and precision are quantitative performance parameters, which are not synonymous. Accuracy is a measure of how close a technique measures to the true count, and has implications for the classification of strongylid egg shedders, but will not affect anthelmintic treatment efficacy evaluation or ascarid monitoring. Precision is a measure of how close repeated counts are to each other, and affects anthelmintic efficacy estimates and strongylid shedding classification. Faecal egg counts do not correlate with worm burdens and do not inform on parasitic involvement in disease. Techniques using test tubes with cover slips placed on top tend to perform with low accuracy and precision in comparison to techniques using counting chambers. Veterinarians should consider the performance of the technique employed for determining faecal egg counts, whether they offer these in house or use a referral diagnostic service. Furthermore, they should consider the training and experience of personnel and protocols in place for diagnostic quality assurance.

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The effect of analyst training on fecal egg counting variability

Cited by 18 publications

References 20 publications

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

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

Comparison of FECPAKG2, a modified Mini-FLOTAC technique and combined sedimentation and flotation for the coproscopic examination of helminth eggs in horses

Parasite faecal egg counts in equine veterinary practice

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