Open Access

Relative egg extraction efficiencies of manual and automated fecal egg count methods in equines


The World Association for the Advancement of Veterinary Parasitology recently released new recommendations for the design of fecal egg count (FEC) reduction tests for livestock. These provide suggestions as to the number of animals to be sampled and the minimum number of eggs that must be counted to produce statistically meaningful results.

One of the considerations for study design is the multiplication factor of the FEC method to be used; methods with lower multiplication factors require fewer animals to be sampled because they are presumed to count more eggs per test. However, multiplication factor is not the sole determinant of the number of eggs counted by any given method, since different techniques use very different sample extraction methodologies that could affect the number of eggs detected beyond just the amount of feces examined.

In this light, we compared three commonly used manual FEC methods (mini-FLOTAC, McMaster and Wisconsin) and two automated methods (Imagyst and Parasight All-in-One) with respect to how many equine strongylid and ascarid eggs they counted in the same samples.

McMaster and mini-FLOTAC (multiplication factors of 25x and 5x, respectively) produced the most accurate results of the methods tested but mini-FLOTAC counted approximately 5-times more eggs than McMaster. However, Wisconsin and Parasight (multiplication factor = 1x) counted 3-times more ova than mini-FLOTAC, which was less than the 5-fold difference in their multiplication factors. As a result, these tests perform with multiplication factors more akin to 1.6x relative to mini-FLOTAC. Imagyst, due to its unique sample preparation methodology, does not have a traditional multiplication factor but performed similarly to McMaster with respect to egg recovery.

Publication timeframe:
4 times per year
Journal Subjects:
Life Sciences, Zoology, Ecology, other, Medicine, Clinical Medicine, Microbiology, Virology and Infection Epidemiology