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Pooled Testing for Quarantine Decisions

Elliot Lipnowski (e.lipnowski@columbia.edu) and Doron Ravid
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Elliot Lipnowski: Columbia University - Department of Economics

No 2020-85, Working Papers from Becker Friedman Institute for Research In Economics

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.

JEL-codes: D04 D61 D62 I18 (search for similar items in EconPapers)
Pages: 34 pages
Date: 2020
New Economics Papers: this item is included in nep-mic
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https://repec.bfi.uchicago.edu/RePEc/pdfs/BFI_WP_202085.pdf (application/pdf)

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