Pooled testing for quarantine decisions

Elliot Lipnowski and Doron Ravid

Journal of Economic Theory, 2021, vol. 198, issue C

Abstract: We study optimal testing to inform quarantine decisions for a population exhibiting a heterogeneous probability of carrying a pathogen. Because test supply is limited, the planner may choose to test a pooled sample, which contains the specimens of multiple individuals (Dorfman, 1943). We characterize the unique optimal allocation of tests. This allocation features assortative batching, whereby agents of differing infection risk are never jointly tested. Moreover, the planner tests only individuals whose prior quarantine decision is the most uncertain. Finally, individuals with higher infection risk are tested in smaller batches, because such tests minimize the informational externality of group testing.

Keywords: Optimal testing; Group testing; Pooled testing; Quarantine; Pandemic; Assortative batching (search for similar items in EconPapers)
JEL-codes: D04 D61 D62 I18 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Working Paper: Pooled Testing for Quarantine Decisions (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jetheo:v:198:y:2021:i:c:s0022053121001897

DOI: 10.1016/j.jet.2021.105372

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