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Evaluating faecal egg count reduction using a specifically designed package "eggCounts" in R and a user friendly web

Paul R Torgerson1, Michaela Paul2, Reinhard Furrer2

  • 1Section of Veterinary Epidemiology, Vetsuisse Faculty, University of Zurich, Switzerland.

International Journal for Parasitology
|February 22, 2014
PubMed
Summary
This summary is machine-generated.

The R package "eggCounts" accurately analyzes fecal egg counts by accounting for random errors and variations between animals. This tool provides reliable estimates for fecal egg count reduction tests, even for users with limited statistical knowledge.

Keywords:
Anthelmintic resistanceBayesian hierarchical modelFaecal egg count reduction testMathematical techniquesStatistical analysis

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Area of Science:

  • Parasitology
  • Statistical modeling
  • Bioinformatics

Background:

  • Faecal egg counts are crucial for assessing parasite burdens but are subject to counting errors and biological variability.
  • Standard analysis methods often fail to account for Poisson errors and over-dispersion inherent in fecal egg count data.
  • Accurate quantification is essential for evaluating treatment efficacy and understanding parasite dynamics.

Purpose of the Study:

  • To introduce the R package "eggCounts" for precise analysis of fecal egg counts.
  • To incorporate sampling error and inter-animal over-dispersion into statistical models.
  • To provide reliable estimation of fecal egg count reduction and associated uncertainty intervals.

Main Methods:

  • Development of the "eggCounts" R package utilizing a hierarchical Bayesian framework.
  • Incorporation of Poisson sampling error and over-dispersion modeling.
  • Creation of a user-friendly web interface for broader accessibility.

Main Results:

  • The "eggCounts" package accurately estimates true fecal egg counts and their probability distributions.
  • It provides robust calculation of 95% uncertainty intervals for counts and reduction percentages.
  • The package effectively handles over-dispersion common in experimental and observational data.

Conclusions:

  • "eggCounts" offers a statistically rigorous approach to analyzing complex fecal egg count data.
  • The package and its web interface democratize advanced statistical analysis for researchers.
  • This tool enhances the reliability of fecal egg count reduction test results in parasitological studies.