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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 (C 1 ), 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 C 1 , X¯ 1-3 , X¯ 1-9 and UCL 1-3 . The results of this study demonstrated that a point estimate (C 1 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 C 1 compared with UCL 1-9 . Of the foals with C 1 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., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background: This study was performed to investigate the efficacy of a morantel-abamectin combination for the treatment of macrocyclic lactone (ML)-resistant Parascaris spp. infections in foals., Methods: Foals on five properties with a Parascaris faecal egg count (FEC) > 50 eggs per gram were used to estimate the FEC reduction (FECR) and efficacy of the anthelmintic combination., Results & Conclusion: On all properties, resistance to ivermectin and abamectin was present and the Parascaris FECR in foals administered the morantel-abamectin combination was > 99%, indicating that this combination effectively controlled ML-resistant parasites., (© 2017 Australian Veterinary Association.)

Faecal egg counts (FEC) are used widely for monitoring of parasite infection in animals, treatment decision-making and estimation of anthelmintic efficacy. When a single count or sample mean is used as a point estimate of the expectation of the egg distribution over some time interval, the variability in the egg density is not accounted for. Although variability, including quantifying sources, of egg count data has been described, the spatiotemporal distribution of nematode eggs in faeces is not well understood. We believe that statistical inference about the mean egg count for treatment decision-making has not been used previously. The aim of this study was to examine the density of Parascaris eggs in solution and faeces and to describe the use of hypothesis testing for decision-making. Faeces from two foals with Parascaris burdens were mixed with magnesium sulphate solution and 30 McMaster chambers were examined to determine the egg distribution in a well-mixed solution. To examine the distribution of eggs in faeces from an individual animal, three faecal piles from a foal with a known Parascaris burden were obtained, from which 81 counts were performed. A single faecal sample was also collected daily from 20 foals on three consecutive days and a FEC was performed on three separate portions of each sample. As appropriate, Poisson or negative binomial confidence intervals for the distribution mean were calculated. Parascaris eggs in a well-mixed solution conformed to a homogeneous Poisson process, while the egg density in faeces was not homogeneous, but aggregated. This study provides an extension from homogeneous to inhomogeneous Poisson processes, leading to an understanding of why Poisson and negative binomial distributions correspondingly provide a good fit for egg count data. The application of one-sided hypothesis tests for decision-making is presented., (Copyright © 2016 Elsevier B.V. All rights reserved.)