Effects of aggregation and sample size on composite faecal egg counts in sheep

Composite faecal egg counts (FEC) are increasingly used to support strategic anthelmintic treatment decisions in grazing livestock. However, their accuracy as estimators of group mean FEC is affected by the number of individual samples included, how thoroughly they are mixed, and the underlying degr...

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Bibliographic Details
Published in:	Veterinary parasitology Vol. 131; no. 1; pp. 79 - 87
Main Authors:	Morgan, E.R., Cavill, L., Curry, G.E., Wood, R.M., Mitchell, E.S.E.
Format:	Journal Article
Language:	English
Published:	Netherlands Elsevier B.V 15-07-2005
Subjects:	accuracy Aggregation Animals Computer Simulation estimation Faecal egg count fecal egg count fecal egg density Feces - parasitology Female flocks frequency distribution gastrointestinal nematodes Helminthiasis - diagnosis Helminthiasis - parasitology Helminths - growth & development Intestinal Diseases, Parasitic - diagnosis Intestinal Diseases, Parasitic - parasitology Intestinal Diseases, Parasitic - veterinary Models, Statistical Negative binomial distribution nematode infections parasite aggregation Parasite Egg Count - methods Parasite Egg Count - standards Parasite Egg Count - veterinary Sample Size Sample size bias sampling sampling bias Sheep Sheep Diseases - diagnosis Sheep Diseases - parasitology simulation models Specimen Handling - methods Specimen Handling - veterinary statistical analysis statistical error Strategic nematode control Faecal egg count Aggregation Strategic nematode control Sample size bias Negative binomial distribution
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Summary:	Composite faecal egg counts (FEC) are increasingly used to support strategic anthelmintic treatment decisions in grazing livestock. However, their accuracy as estimators of group mean FEC is affected by the number of individual samples included, how thoroughly they are mixed, and the underlying degree of parasite aggregation between individual hosts. This paper uses a Negative Binomial model for parasite aggregation, and a Poisson model for egg distribution within faecal suspensions, in order to optimise composite FEC protocol for commercial sheep flocks. Our results suggest that faecal egg density in a well-mixed composite sample from 10 sheep (3 g of faeces from each), estimated by examination of four independently filled McMaster chambers, is likely to provide an adequate estimate of group mean FEC in the majority of situations. However, extra care is needed in groups of sheep for which high levels of FEC aggregation might be expected. The implications of statistical error in FEC estimates depend on how they are used. The simulation-based approach presented here is a powerful tool for investigating the risks of error in FEC-driven treatment decisions in different situations, as well as for the statistical analysis of parasitological data in general.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	0304-4017 1873-2550
DOI:	10.1016/j.vetpar.2005.04.021