Pooled testing efficiency increases with test frequency

Ned Augenblick, Jonathan Kolstad, Ziad Obermeyer and Ao Wang
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Ned Augenblick: a Haas School of Business, University of California, Berkeley, CA 94720;
Ziad Obermeyer: c School of Public Health, University of California, Berkeley, CA 94704
Ao Wang: b Department of Economics, University of California, Berkeley, CA 94720;

Proceedings of the National Academy of Sciences, 2022, vol. 119, issue 2, e2105180119

Abstract: Frequent mass testing can slow a rapidly spreading infectious disease by quickly identifying and isolating infected individuals from the population. One proposed method to reduce the extremely high costs of this testing strategy is to employ pooled testing, in which samples are combined and tested together using one test, and the entire pool is cleared given a negative test result. This paper demonstrates that frequent pooled testing of individuals with correlated risk—even given large uncertainty about infection rates—is particularly efficient. We conclude that frequent pooled testing using natural groupings is a cost-effective way to suppress infection risk in a pandemic.

Keywords: pooled testing; COVID-19; surveillance testing (search for similar items in EconPapers)
Date: 2022
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