publications.RmdHere you can find a list of publications related to eggCounts package, order by most recent.
Modelling anthelmintic resistance by extending eggCounts package to allow individual efficacy
Abstract: The same anthelmintic treatment can have variable efficacy on individual animals even if the parasite population is homogenously susceptible. An extension of the R package eggCounts is proposed to take individual efficacy into account using a Bayesian hierarchical model. A simulation study is conducted to compare the performance of five different methods on estimating faecal egg count reduction and its uncertainty interval. Simulation results showed the individual efficacy model offered robust inference to two different data simulation procedures with low root mean squared error on the reduction estimate and appropriate uncertainty estimates. Different methods were used to evaluate the anthelmintic resistance in a dataset from USA with sheep and cattle faecal egg counts, where a strong anthelmintic resistance was detected. Open-source statistical tools were updated to include the proposed model.
Wang, C., Torgerson, P. R., Kaplan, R. M., George, M. M., & Furrer, R. (2018). Modelling anthelmintic resistance by extending eggCounts package to allow individual efficacy. International Journal for Parasitology: Drugs and Drug Resistance.
eggCounts: a Bayesian hierarchical toolkit to model faecal egg count reductions
Abstract: This is a vignette for the R package eggCounts version 2.0. The package implements a suite of Bayesian hierarchical models dealing with faecal egg count reductions. The models are designed for a variety of practical situations, including individual treatment efficacy, zero inflation, small sample size (less than 10) and potential outliers. The functions are intuitive to use and their output are easy to interpret, such that users are protected from being exposed to complex Bayesian hierarchical modelling tasks. In addition, the package includes plotting functions to display data and results in a visually appealing manner. The models are implemented in Stan modelling language, which provides efficient sampling technique to obtain posterior samples. This vignette briefly introduces different models, and provides a short walk-through analysis with example data.
Wang, C., & Furrer, R. (2018). eggCounts: a Bayesian hierarchical toolkit to model faecal egg count reductions. arXiv:1804.11224 [stat.CO].
Zero-inflated hierarchical models for faecal egg counts to assess anthelmintic efficacy
Abstract: The prevalence of anthelmintic resistance has increased in recent years, as a result of the extensive use of anthelmintic drugs to reduce the infection of parasitic worms in livestock. In order to detect the resistance, the number of parasite eggs in animal faeces is counted. Typically a subsample of the diluted faeces is examined, and the mean egg counts from both untreated and treated animals are compared. However, the conventional method ignores the variabilities introduced by the counting process and by different infection levels across animals. In addition, there can be extra zero counts, which arise as a result of the unexposed animals in an infected population or animals. In this paper, we propose the zero-inflated Bayesian hierarchical models to estimate the reduction in faecal egg counts. The simulation study compares the Bayesian models with the conventional faecal egg count reduction test and other methods such as bootstrap and quasi-Poisson regression. The results show the Bayesian models are more robust and they perform well in terms of both the bias and the coverage. We further illustrate the advantages of our proposed model using a case study about the anthelmintic resistance in Swedish sheep flocks.
Wang, C., Torgerson, P. R., Höglund, J., & Furrer, R. (2017). Zero-inflated hierarchical models for faecal egg counts to assess anthelmintic efficacy. Veterinary parasitology, 235, 20-28.
Abstract: The seemingly straightforward task of analysing faecal egg counts resulting from laboratory procedures such as the McMaster technique has, in reality, a number of complexities. These include Poisson errors in the counting technique which result from eggs being randomly distributed in well mixed faecal samples. In addition, counts between animals in a single experimental or observational group are nearly always over-dispersed. We describe the R package “eggCounts” that we have developed that incorporates both sampling error and over-dispersion between animals to calculate the true egg counts in samples of faeces, the probability distribution of the true counts and summary statistics such as the 95% uncertainty intervals. Based on a hierarchical Bayesian framework, the software will also rigorously estimate the percentage reduction of faecal egg counts and the 95% uncertainty intervals of data generated by a faecal egg count reduction test. We have also developed a user friendly web interface that can be used by those with limited knowledge of the R statistical computing environment. We illustrate the package with three simulated data sets of faecal egg count reduction experiments.
Torgerson, P. R., Paul, M., & Furrer, R. (2014). Evaluating faecal egg count reduction using a specifically designed package “eggCounts” in R and a user friendly web interface. International journal for parasitology, 44(5), 299-303.