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Economic Benefits of COVID-19 Screening Tests

Author

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  • Andrew Atkeson
  • Michael C. Droste
  • Michael Mina
  • James H. Stock

Abstract

We assess the economic value of screening testing programs as a policy response to the ongoing COVID-19 pandemic. We find that the fiscal, macroeconomic, and health benefits of rapid SARS-CoV-2 screening testing programs far exceed their costs, with the ratio of economic benefits to costs typically in the range of 4-15 (depending on program details), not counting the monetized value of lives saved. Unless the screening test is highly specific, however, the signal value of the screening test alone is low, leading to concerns about adherence. Confirmatory testing increases the net economic benefits of screening tests by reducing the number of healthy workers in quarantine and by increasing adherence to quarantine measures. The analysis is undertaken using a behavioral SIR model for the United States with 5 age groups, 66 economic sectors, screening and diagnostic testing, and partial adherence to instructions to quarantine or to isolate.

Suggested Citation

  • Andrew Atkeson & Michael C. Droste & Michael Mina & James H. Stock, 2020. "Economic Benefits of COVID-19 Screening Tests," NBER Working Papers 28031, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:28031
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    References listed on IDEAS

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    1. David Berger & Kyle Herkenhoff & Chengdai Huang & Simon Mongey, 2022. "Testing and Reopening in an SEIR Model," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 43, pages 1-21, January.
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    8. Daron Acemoglu & Ali Makhdoumi & Azarakhsh Malekian & Asuman Ozdaglar, 2024. "Testing, Voluntary Social Distancing, and the Spread of an Infection," Operations Research, INFORMS, vol. 72(2), pages 533-548, March.
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    10. Goolsbee, Austan & Syverson, Chad, 2021. "Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020," Journal of Public Economics, Elsevier, vol. 193(C).
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    Cited by:

    1. Steven Stillman & Mirco Tonin, 2022. "Communities and testing for COVID-19," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(4), pages 617-625, June.
    2. Ricardo Martínez & Juan D Moreno Ternero, 2021. "Pandemic performance," ThE Papers 21/09, Department of Economic Theory and Economic History of the University of Granada..
    3. Jiayi Lin & Hrayer Aprahamian & George Golovko, 2024. "An optimization framework for large-scale screening under limited testing capacity with application to COVID-19," Health Care Management Science, Springer, vol. 27(2), pages 223-238, June.
    4. Martínez, Ricardo & Moreno-Ternero, Juan D., 2022. "An axiomatic approach towards pandemic performance indicators," Economic Modelling, Elsevier, vol. 116(C).
    5. Shami, Labib & Lazebnik, Teddy, 2022. "Economic aspects of the detection of new strains in a multi-strain epidemiological–mathematical model," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    6. Francesco Furno, 2020. "The Testing Multiplier: Fear vs Containment," Papers 2012.03834, arXiv.org.
    7. James Broughel & Michael Kotrous, 2021. "The benefits of coronavirus suppression: A cost-benefit analysis of the response to the first wave of COVID-19 in the United States," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-20, June.
    8. Hasnan Baber, 2021. "Efficacy of COVID-19 screening system and customer satisfaction in banks: moderating role of the perceived threat and health risk," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 26(4), pages 295-304, December.
    9. Ely, Jeffrey & Galeotti, Andrea & Jann, Ole & Steiner, Jakub, 2021. "Optimal test allocation," Journal of Economic Theory, Elsevier, vol. 193(C).
    10. Eslami, Keyvan & Lee, Hyunju, 2024. "Overreaction and the value of information in a pandemic," European Economic Review, Elsevier, vol. 161(C).
    11. Fallucchi, Francesco & Görges, Luise & Machado, Joël & Pieters, Arne & Suhrcke, Marc, 2021. "How to make universal, voluntary testing for COVID-19 work? A behavioural economics perspective," Health Policy, Elsevier, vol. 125(8), pages 972-980.
    12. Xin, Meiqi & Lau, Joseph Tak-fai & Lau, Mason M.C., 2022. "Multi-dimensional factors related to participation in a population-wide mass COVID-19 testing program among Hong Kong adults: A population-based randomized survey," Social Science & Medicine, Elsevier, vol. 294(C).
    13. Martin Kahanec & Lukáš Lafférs & Bernhard Schmidpeter, 2021. "The impact of repeated mass antigen testing for COVID-19 on the prevalence of the disease," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(4), pages 1105-1140, October.
    14. Soltanisehat, Leili & González, Andrés D. & Barker, Kash, 2023. "Modeling social, economic, and health perspectives for optimal pandemic policy decision-making," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).

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    More about this item

    JEL classification:

    • E60 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General
    • I10 - Health, Education, and Welfare - - Health - - - General

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