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Group Testing for Identification

Grouping (pooling) items together and testing them as one unit for a binary trait is the process known concurrently as group testing and pooled testing. As long as trait prevalence is small, group testing can lead to significant reductions in the number of tests when compared to testing each item individually. The purpose of this article is to outline commonly used group-testing algorithms and describe how to calculate their corresponding operating characteristics. Focus is on using group testing to identify whether an item has a particular trait rather than estimating the probability an item has this trait.