Remarks on pooling Coronavirus tests

Abstract

AbstractDiagnostic testing for the novel Coronavirus is an important tool to fight the Covid-19 pandemic. However, testing capacities are limited. A modified testing protocol, whereby a number of probes are “pooled” (that is, grouped), is known to increase the capacity for testing. Here, we model pooled testing with a double-average model, which we think to be close to reality for Covid-19 testing. The optimal pool size and the effect of test errors are considered. Results show that the best pool size is three to five, under reasonable assumptions. Pool testing even reduces the number of false positives in the absence of dilution effects.