Pooled Testing for Quarantine Decisions

34 Pages Posted: 14 Jul 2020 Last revised: 17 Jun 2021

See all articles by Elliot Lipnowski

Elliot Lipnowski

Columbia University

Doron Ravid

University of Chicago - Department of Economics

Multiple version iconThere are 2 versions of this paper

Date Written: July 3, 2020

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, batched testing, quarantine, pandemic, assortative batching

JEL Classification: D04, D61, I18, D62

Suggested Citation

Lipnowski, Elliot and Ravid, Doron, Pooled Testing for Quarantine Decisions (July 3, 2020). University of Chicago, Becker Friedman Institute for Economics Working Paper Forthcoming, Available at SSRN: https://ssrn.com/abstract=3633360 or http://dx.doi.org/10.2139/ssrn.3633360

Elliot Lipnowski (Contact Author)

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

Doron Ravid

University of Chicago - Department of Economics ( email )

1126 E. 59th St
Chicago, IL 60637
United States

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