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Pooled testing for quarantine decisions

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  • Lipnowski, Elliot
  • Ravid, Doron

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

  • Lipnowski, Elliot & Ravid, Doron, 2021. "Pooled testing for quarantine decisions," Journal of Economic Theory, Elsevier, vol. 198(C).
    • Handle: RePEc:eee:jetheo:v:198:y:2021:i:c:s0022053121001897
    DOI: 10.1016/j.jet.2021.105372
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    References listed on IDEAS

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    2. Davide Bosco & Luca Portoghese, 2024. "Complementarity, Congestion and Information Design in Epidemics with Strategic Social Behaviour," DEM Working Papers Series 218, University of Pavia, Department of Economics and Management.

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    More about this item

    Keywords

    Optimal testing; Group testing; Pooled testing; Quarantine; Pandemic; Assortative batching;
    All these keywords.

    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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