In the early stages of a novel pandemic, testing is simultaneously in high demand and low supply, making efficient use of tests of paramount importance. One approach to improve the efficiency of tests is to mix samples from multiple individuals, only testing individuals when the pooled sample returns a positive. To reflect potential clusters of cases that might queue at a testing site and that might increase the efficiency of batch testing, I simulate 10,000 persons being tested in sequence. I use a prevalence ranging from 1% to 45% and batch sizes ranging from 3 to 25 and assume the increased probability of consecutive infections ranges from 0% to 45%. I find that as the likelihood of clustered infections increases, the efficiency of specimen pooling increases. This analysis suggests that when clusters of infected persons exist at testing sites, specimen pooling can remain efficient even as prevalence increases. See video abstract: http://links.lww.com/EDE/B729.
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