Statistical design for health monitoring in laboratory animal facilities using sentinel animals

Abstract

Regular health monitoring is crucial in laboratory animal facilities to determine the presence or absence of specific pathogens. One common approach to monitoring involves the use of sentinel animals, which are periodically exposed to biological material from the cages being monitored. At a certain point, some of these sentinel animals are tested for pathogens. This article discusses designing an effective sampling scheme to meet desired quality standards. It addresses questions such as the number of sentinel animals required, the frequency of sampling biological material, the selection of cages based on facility set-up, and the optimal frequency and quantity of sentinel animal tests. While existing design formulas are available for simple random sampling, no quantitative recommendation exists for using sentinel animals to the best of our knowledge. We propose a Monte Carlo simulation-based approach in this article to address this. Our algorithm has been implemented in a publicly accessible web page at http://nolan.cnb.csic.es/sentinelcagesmanager.