Torgerson Paul R, Paul Michaela, Furrer Reinhard
Section of Veterinary Epidemiology, Vetsuisse Faculty, University of Zurich, Switzerland.
Institute of Mathematics, University of Zurich, Switzerland.
Int J Parasitol. 2014 Apr;44(5):299-303. doi: 10.1016/j.ijpara.2014.01.005. Epub 2014 Feb 17.
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.
通过麦克马斯特技术等实验室程序分析粪便虫卵计数这一看似简单直接的任务,实际上存在诸多复杂之处。这些复杂之处包括计数技术中的泊松误差,这是由于虫卵在充分混合的粪便样本中随机分布所致。此外,在单个实验或观察组内的动物之间的计数几乎总是过度离散的。我们描述了我们开发的R包“eggCounts”,它纳入了抽样误差和动物之间的过度离散,以计算粪便样本中的真实虫卵计数、真实计数的概率分布以及诸如95%不确定区间等汇总统计量。基于分层贝叶斯框架,该软件还将严格估计粪便虫卵计数的减少百分比以及粪便虫卵计数减少试验产生的数据的95%不确定区间。我们还开发了一个用户友好的网络界面,供那些对R统计计算环境了解有限的人使用。我们用三个粪便虫卵计数减少实验的模拟数据集来说明这个包。