A quantitative approach to improving the analysis of faecal worm egg count data

Analysis of Faecal Egg Count (FEC) and Faecal Egg Count Reduction Test (FECRT) datasets is frequently complicated by a high degree of variability between observations and relatively small sample sizes. In this thesis, statistical issues pertaining to the analysis of FEC and FECRT data are examined, and improved methods of analysis using Bayesian Markov chain Monte Carlo (MCMC) are developed. Simulated data were used to compare the accuracy of MCMC methods to existing maximum likelihood methods. The potential consequences of model selection based on empirical fit were also examined by comparing inference made from simulated data using different distributional assumptions. The novel methods were then applied to FEC data obtained from sheep and horses. Several syntactic variations of FECRT models were also developed, incorporating various different distributional assumptions including meta-population models. The inference made from simulated data and FECRT data taken from horses was compared to that made using the currently most widely used methods. Multi-level hierarchical models were then used to partition the source of the observed variability in FEC using data intensively sampled from a small group of horses. The MCMC methods out-performed other methods for analysis of simulated FEC and FECRT datasets, particularly in terms of the usefulness of 95% confidence intervals produced. There was no consistent difference in model fit to the gamma-Poisson or lognormal-Poison distributions from the available data. However there was evidence for the existence of bi-modality in the datasets. Although the majority of the observed variation in equine FEC is likely a consequence of variability between animals, a considerable proportion of the variability is due to the variability in true FEC between faecal piles and the aggregation of eggs on a local scale within faeces. The methods currently used for analysis of FEC and FECRT data perform poorly compared to MCMC methods, and produce 95% confidence intervals which are unreliable for datasets likely to be encountered in clinical parasitology. MCMC analysis is therefore to be preferred for these types of data, and also allows multiple samples taken from each animal to be incorporated into the analysis. Analysing the statistical processes underlying FEC data also revealed simple methods of reducing the observed variability, such as increasing the size of individual samples of faeces. Modelling the variability structure of FEC data, and use of the inferred parameter values in precision analysis and power analysis calculations, allows the usefulness of a study to be quantified before the data are collected. Given the difficulties with analysing FEC and FECRT data demonstrated, it is essential that such consideration of the statistical issues pertaining to the collection and analysis of such data is made for future parasitological studies

The effectiveness of faecal removal methods of pasture management to control the cyathostomin burden of donkeys

Background: The level of anthelmintic resistance within some cyathostomin parasite populations has increased to the level where sole reliance on anthelmintic-based control protocols is not possible. Management-based nematode control methods, including removal of faeces from pasture, are widely recommended for use in association with a reduction in anthelmintic use to reduce selection pressure for drug resistance; however, very little work has been performed to quantitatively assess the effectiveness of such methods.<p></p> Methods: We analysed data obtained from 345 donkeys at The Donkey Sanctuary (Devon, UK), managed under three different pasture management techniques, to investigate the effectiveness of faeces removal in strongyle control in equids. The management groups were as follows: no removal of faeces from pasture, manual, twice-weekly removal of faeces from pasture and automatic, twice-weekly removal of faeces from pasture (using a mechanical pasture sweeper). From turn-out onto pasture in May, monthly faecal egg counts were obtained for each donkey and the dataset subjected to an auto regressive moving average model.<p></p> Results: There was little to no difference in faecal egg counts between the two methods of faecal removal; both resulted in significantly improved cyathostomin control compared to the results obtained from the donkeys that grazed pasture from which there was no faecal removal.<p></p> Conclusions: This study represents a valuable and unique assessment of the effectiveness of the removal of equine faeces from pasture, and provides an evidence base from which to advocate twice-weekly removal of faeces from pasture as an adjunct for equid nematode control. Widespread adoption of this practice could substantially reduce anthelmintic usage, and hence reduce selection pressure for nematode resistance to the currently effective anthelmintic products.<p></p&gt

A Bayesian generalized random regression model for estimating heritability using overdispersed count data

Background: Faecal egg counts are a common indicator of nematode infection and since it is a heritable trait, it provides a marker for selective breeding. However, since resistance to disease changes as the adaptive immune system develops, quantifying temporal changes in heritability could help improve selective breeding programs. Faecal egg counts can be extremely skewed and difficult to handle statistically. Therefore, previous heritability analyses have log transformed faecal egg counts to estimate heritability on a latent scale. However, such transformations may not always be appropriate. In addition, analyses of faecal egg counts have typically used univariate rather than multivariate analyses such as random regression that are appropriate when traits are correlated. We present a method for estimating the heritability of untransformed faecal egg counts over the grazing season using random regression. Results: Replicating standard univariate analyses, we showed the dependence of heritability estimates on choice of transformation. Then, using a multitrait model, we exposed temporal correlations, highlighting the need for a random regression approach. Since random regression can sometimes involve the estimation of more parameters than observations or result in computationally intractable problems, we chose to investigate reduced rank random regression. Using standard software (WOMBAT), we discuss the estimation of variance components for log transformed data using both full and reduced rank analyses. Then, we modelled the untransformed data assuming it to be negative binomially distributed and used Metropolis Hastings to fit a generalized reduced rank random regression model with an additive genetic, permanent environmental and maternal effect. These three variance components explained more than 80 % of the total phenotypic variation, whereas the variance components for the log transformed data accounted for considerably less. The heritability, on a link scale, increased from around 0.25 at the beginning of the grazing season to around 0.4 at the end. Conclusions: Random regressions are a useful tool for quantifying sources of variation across time. Our MCMC (Markov chain Monte Carlo) algorithm provides a flexible approach to fitting random regression models to non-normal data. Here we applied the algorithm to negative binomially distributed faecal egg count data, but this method is readily applicable to other types of overdispersed data

Farm specific transmission patterns of Fasciola hepatica in Danish dairy cattle based on different diagnostic methods and monitoring of grazing management

A recent survey based on meat inspection data showed that approximately 30% of Danish cattle farms were infected with liver flukes, leading to significant economic losses. Despite the widespread problem, up-to-date knowledge on transmission patterns, diagnostic methods and practical measures for control is still lacking. We therefore initiated a longitudinal, observational study in a few infected dairy farms to elucidate farm specific transmission patterns based on different diagnostic methods and grazing management. Two organic and two conventional dairy farms with high F. hepatica antibody levels in bulk tank milk were selected. From each farm a cohort of 40 animals from different age groups (calves, heifers, primiparous and multiparous cows) were sampled 7 times between April 2015 and January 2017. Diagnostic methods included faecal egg count by sedimentation, serum ELISA and coproantigen ELISA. Additionally, monthly bulk tank milk samples were analyzed by ELISA. The analyses are ongoing, but preliminary results indicate that F. hepatica is mainly transmitted via summer infection of snails as most animals seroconvert in late autumn without shedding of eggs. However, infection early in the grazing season due to overwintered snails has also been observed. One farm where cows are stabled have had some older cows continuing to shed F. hepatica eggs, suggesting long life span of F. hepatica, although other routes of infection cannot be ruled out. The final results will provide novel and practical information about different diagnostic tests and transmission patterns related to grazing management on farm-level

Genotype variation and genetic relationship among Escherichia coli from nursery pigs located in different pens in the same farm

BACKGROUND: So far, little is known about the genetic diversity and relatedness among Escherichia coli (E. coli) populations in the gut of swine. Information on this is required to improve modeling studies on antimicrobial resistance aiming to fight its occurrence and development. This work evaluated the genotype variation of E. coli isolated from swine fecal samples at the single pig and pen level, as well as between pens using repetitive extragenic palindromic (REP) PCR fingerprinting and pulsed field gel electrophoresis (PFGE). The genetic diversity of strains collected from media supplemented with ampicillin or tetracycline was also investigated. Besides, the genetic relationship of strains within each pen, between pens, as well as among strains within each group isolated from media with or without antibiotic, was assessed. RESULTS: REP-PCR patterns (N = 75) were generated for all the isolates (N = 720). Two profiles (REP_2 and REP_5) dominated, accounting for 23.7 and 23.3% of all isolates, respectively. At the pig and at the pen level, the number of different strains ranged from two to eight, and from 27 to 31, respectively, and multiple isolates from a single pen were found to be identical; however, in some of the pens, additional strains occurred at a lower frequency. E. coli isolates yielding different REP profiles were subjected to PFGE and led to 41 different genotypes which were also compared. CONCLUSIONS: Despite the presence of dominant strains, our results suggest a high genetic diversity of E. coli strains exist at the pen level and between pens. Selection with antibiotic seems to not affect the genetic diversity. The dominant REP profiles were the same found in a previous study in Denmark, which highlights that the same predominant strains are circulating in pigs of this country and might represent the archetypal E.coli commensal in pigs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12866-016-0912-3) contains supplementary material, which is available to authorized users

Genotype variation and genetic relationship among Escherichia coli from nursery pigs located in different pens in the same farm

Abstract Background So far, little is known about the genetic diversity and relatedness among Escherichia coli ( E. coli ) populations in the gut of swine. Information on this is required to improve modeling studies on antimicrobial resistance aiming to fight its occurrence and development. This work evaluated the genotype variation of E. coli isolated from swine fecal samples at the single pig and pen level, as well as between pens using repetitive extragenic palindromic (REP) PCR fingerprinting and pulsed field gel electrophoresis (PFGE). The genetic diversity of strains collected from media supplemented with ampicillin or tetracycline was also investigated. Besides, the genetic relationship of strains within each pen, between pens, as well as among strains within each group isolated from media with or without antibiotic, was assessed. Results REP-PCR patterns ( N \u2009=\u200975) were generated for all the isolates ( N \u2009=\u2009720). Two profiles (REP_2 and REP_5) dominated, accounting for 23.7 and 23.3% of all isolates, respectively. At the pig and at the pen level, the number of different strains ranged from two to eight, and from 27 to 31, respectively, and multiple isolates from a single pen were found to be identical; however, in some of the pens, additional strains occurred at a lower frequency. E. coli isolates yielding different REP profiles were subjected to PFGE and led to 41 different genotypes which were also compared. Conclusions Despite the presence of dominant strains, our results suggest a high genetic diversity of E. coli strains exist at the pen level and between pens. Selection with antibiotic seems to not affect the genetic diversity. The dominant REP profiles were the same found in a previous study in Denmark, which highlights that the same predominant strains are circulating in pigs of this country and might represent the archetypal E.coli commensal in pigs

Pathway of oxfendazole from the host into the worm:<i>Trichuris suis</i> in pigs

It is well known that the efficacy of a single oral dose of benzimidazoles against Trichuris spp. infections in humans and animals is poor, but is currently still used in control programmes against human trichuriasis. However, the route of the benzimidazoles from the treated host to Trichuris remains unknown. As parts of adult Trichuris are situated intracellularly in the caecum, they might be exposed to anthelmintic drugs in the intestinal content as well as the mucosa. In this study, the pathway of oxfendazole and its metabolites was explored using a T. suis-pig infection model, by simultaneously measuring drug concentrations within the worms and the caecal mucosa, caecal tissue, caecal content and plasma of pigs over time after a single oral dose of 5 mg/kg oxfendazole. Additionally, for comparison to the in vivo study, drug uptake and metabolism of oxfendazole by T. suis was examined after in vitro incubation. Oxfendazole and metabolites were quantified by High Performance Liquid Chromatography.Multivariate linear regression analysis showed a strong and highly significant association between OFZ concentrations within T. suis and in plasma, along with a weaker association between OFZ concentrations in caecal tissue/mucosa and T. suis, suggesting that oxfendazole reaches T. suis after absorption from the gastrointestinal tract and enters the worms by the blood-enterocyte pathway. The fenbendazole sulfone level in T. suis was highly affected by the concentrations in plasma. In addition, correlations between drug concentrations in the host compartments, were generally highest for this metabolite. In comparison to oxfendazole, the correlation between plasma and content was particularly high for this metabolite, suggesting a high level of drug movement between these compartments and the possible involvement of the enterohepatic circulation. Keywords: Trichuris, Benzimidazole, Drug efficacy, Drug pathwa

The prevalences of Salmonella Genomic Island 1 variants in human and animal Salmonella Typhimurium DT104 are distinguishable using a Bayesian approach

Throughout the 1990s, there was an epidemic of multidrug resistant Salmonella Typhimurium DT104 in both animals and humans in Scotland. The use of antimicrobials in agriculture is often cited as a major source of antimicrobial resistance in pathogenic bacteria of humans, suggesting that DT104 in animals and humans should demonstrate similar prevalences of resistance determinants. Until very recently, only the application of molecular methods would allow such a comparison and our understanding has been hindered by the fact that surveillance data are primarily phenotypic in nature. Here, using large scale surveillance datasets and a novel Bayesian approach, we infer and compare the prevalence of Salmonella Genomic Island 1 (SGI1), SGI1 variants, and resistance determinants independent of SGI1 in animal and human DT104 isolates from such phenotypic data. We demonstrate differences in the prevalences of SGI1, SGI1-B, SGI1-C, absence of SGI1, and tetracycline resistance determinants independent of SGI1 between these human and animal populations, a finding that challenges established tenets that DT104 in domestic animals and humans are from the same well-mixed microbial population