Statistical approach to measure the efficacy of anthelmintic treatment on horse farms

Resistance to anthelmintics in gastrointestinal nematodes of livestock is a serious problem and appropriate methods are required to identify and quantify resistance. However, quantification and assessment of resistance depend on an accurate measure of treatment efficacy, and current methodologies fail to properly address the issue. The fecal egg count reduction test (FECRT) is the practical gold standard for measuring anthelmintic efficacy on farms, but these types of data are fraught with high variability that greatly impacts the accuracy of inference on efficacy. This paper develops a statistical model to measure, assess, and evaluate the efficacy of the anthelmintic treatment on horse farms as determined by FECRT. Novel robust bootstrap methods are developed to analyse the data and are compared to other suggested methods in the literature in terms of Type I error and power. The results demonstrate that the bootstrap methods have an optimal Type I error rate and high power to detect differences between the presumed and true efficacy without the need to know the true distribution of pre-treatment egg counts. Finally, data from multiple farms are studied and statistical models developed that take into account between-farm variability. Our analysis establishes that if inter-farm variability is not taken into account, misleading conclusions about resistance can be made.