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Pooled Testing for Quarantine Decisions

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  • Elliot Lipnowski

    (Columbia University - Department of Economics)

  • Doron Ravid

    (University of Chicago - Department of 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.

Suggested Citation

  • Elliot Lipnowski & Doron Ravid, 2020. "Pooled Testing for Quarantine Decisions," Working Papers 2020-85, Becker Friedman Institute for Research In Economics.
    • Handle: RePEc:bfi:wpaper:2020-85
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • D04 - Microeconomics - - General - - - Microeconomic Policy: Formulation; Implementation; Evaluation
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • D62 - Microeconomics - - Welfare Economics - - - Externalities

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