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Test Sensitivity for Infection versus Infectiousness of SARS-CoV-2

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  • Joshua S. Gans

Abstract

The most commonly used test for the presence of SARS-CoV-2 is a PCR test that is able to detect very low viral loads and inform on treatment decisions. Medical research has confirmed that many individuals might be infected with SARS-CoV-2 but not infectious. Knowing whether an individual is infectious is the critical piece of information for a decision to isolate an individual or not. This paper examines the value of different tests from an information-theoretic approach and shows that applying treatment-based approval standards for tests for infection will lower the value of those tests and likely causes decisions based on them to have too many false positives (i.e., individuals isolated who are not infectious). The conclusion is that test scoring be tailored to the decision being made.

Suggested Citation

  • Joshua S. Gans, 2020. "Test Sensitivity for Infection versus Infectiousness of SARS-CoV-2," NBER Working Papers 27780, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:27780
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    References listed on IDEAS

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    1. Martin S Eichenbaum & Sergio Rebelo & Mathias Trabandt, 2021. "The Macroeconomics of Epidemics [Economic activity and the spread of viral diseases: Evidence from high frequency data]," The Review of Financial Studies, Society for Financial Studies, vol. 34(11), pages 5149-5187.
    2. Maximilian Kasy & Alexander Teytelboym, 2020. "Adaptive targeted infectious disease testing," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 36(Supplemen), pages 77-93.
    3. Ely, Jeffrey & Galeotti, Andrea & Jann, Ole & Steiner, Jakub, 2021. "Optimal test allocation," Journal of Economic Theory, Elsevier, vol. 193(C).
    4. Gans, Joshua Samuel, 2020. "The Economic Consequences of R=1: Towards a Workable Behavioural Epidemiological Model of Pandemics," SocArXiv yxdc5, Center for Open Science.
    5. Maximilian Kasy & Alexander Teytelboym, 0. "Adaptive targeted infectious disease testing," Oxford Review of Economic Policy, Oxford University Press, vol. 36(Supplemen), pages 77-93.
    6. Bergstrom, Ted & Bergstrom, Carl & Li, Haoran, 2020. "Frequency and Accuracy in Proactive Testing for COVID-19," University of California at Santa Barbara, Economics Working Paper Series qt8nf4c0jd, Department of Economics, UC Santa Barbara.
    7. Michael A. Boozer & Tomas J. Philipson, 2000. "The Impact of Public Testing for Human Immunodeficiency Virus," Journal of Human Resources, University of Wisconsin Press, vol. 35(3), pages 419-446.
    8. Giorgia Guglielmi, 2021. "Rapid coronavirus tests: a guide for the perplexed," Nature, Nature, vol. 590(7845), pages 202-205, February.
    9. Daron Acemoglu & Ali Makhdoumi & Azarakhsh Malekian & Asuman Ozdaglar, 2020. "Testing, Voluntary Social Distancing and the Spread of an Infection," NBER Working Papers 27483, National Bureau of Economic Research, Inc.
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    RePEc Biblio mentions

    As found on the RePEc Biblio, the curated bibliography for Economics:
    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Health > Testing

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    Cited by:

    1. Andrew Atkeson & Michael Droste & Michael J. Mina & James H. Stock, 2020. "Economic Benefits of COVID-19 Screening Tests," Staff Report 616, Federal Reserve Bank of Minneapolis.
    2. Jonas Hedlund & Allan Hernández-Chanto & Carlos Oyarzún, 2021. "Contagion Management through Information Disclosure," Discussion Papers Series 651, School of Economics, University of Queensland, Australia.
    3. Francesco Flaviano Russo, 2020. "Testing Policies During an Epidemic," CSEF Working Papers 591, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    4. Bergstrom, Ted & Bergstrom, Carl & Li, Haoran, 2020. "Frequency and Accuracy in Proactive Testing for COVID-19," University of California at Santa Barbara, Economics Working Paper Series qt8nf4c0jd, Department of Economics, UC Santa Barbara.

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    More about this item

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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