Best Student Presentation Award winners

2016 – Johnathan Love, University of Strathclyde

Winners’ abstracts

(2016) Probability distributions of faecal egg count data and their impact on investigating anthelmintic efficacy

Johnathan Love, Louise Kelly, Chris Robertson, Ian Nanjiani, Mike Taylor and Hannah Lester.

University of Strathclyde, Westpoint Research and VParsT Ltd.

Over the past 60 years, the use of anthelmintics has been increasingly under threat due to parasite populations becoming resistant to products in use.The Faecal Egg Count Reduction Test (FECRT) has been the most widely used field-based method for determining anthelmintic efficacy and as an indicator of the presence of anthelmintic resistant nematodes in livestock, based on the World Association for Advancement in Veterinary Parasitology (WAAVP) guidelines. These guidelines make recommendations on both test performance and statistical analysis and data interpretation in an effort to quantify levels of resistance present at the farm level. Whilst aimed primarily at sheep, the guidelines are also used for FECRT in cattle. However, due to differences in levels of faecal egg outputs between sheep and cattle and the limits of detection in faecal egg count (FEC) methods; the guidelines applied to cattle have come under much review. A collaborative project involving the authors has  been set up in which one of the aims is to evaluate a range of  analytical and statistical methods on extensive field data collected over 3 grazing seasons in which cattle were screened, treated and monitored for parasitic nematode infections using several FEC  methods and sensitivities. This investigation has shown that for cattle FECs obtained using a counting technique with high precision (1epg); distributions associated with the Negative binomial are of better representation and hence, arithmetic mean estimates should be used when calculating percentage reductions for a FECRT. However, if cattle FECs are obtained with less precise counting techniques (30 or 15epg), then it is recommended to take the arithmetic group mean and divide this by the proportion of non-zero counts present in FEC data (zero-inflated distributions), otherwise anthelmintic efficacy could be exaggerated.