IDEAS home Printed from https://ideas.repec.org/a/spr/reecde/v28y2024i4d10.1007_s10058-024-00361-1.html
   My bibliography  Save this article

Economic benefits of COVID-19 screening tests

Author

Listed:
  • Andrew Atkeson

    (UCLA)

  • Michael Droste

    (Harvard University)

  • Michael J. Mina

    (eMed)

  • James H. Stock

    (Harvard University)

Abstract

We assess the economic value of screening testing programs as a policy response to the COVID-19 pandemic, first before vaccines were available then during the vaccine rollout. We find that, before vaccines, the fiscal, macroeconomic, and health benefits of rapid SARS-CoV-2 screening testing programs would have far exceeded their costs, with the ratio of economic benefits to costs typically in the range of 2–15 (depending on program details), not counting the monetized value of lives saved. The macroeconomic cost–benefit analysis remains strongly positive after vaccines become available, although the increase in tax revenue might not fully cover the program cost. 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 Droste & Michael J. Mina & James H. Stock, 2024. "Economic benefits of COVID-19 screening tests," Review of Economic Design, Springer;Society for Economic Design, vol. 28(4), pages 689-722, December.
  • Handle: RePEc:spr:reecde:v:28:y:2024:i:4:d:10.1007_s10058-024-00361-1
    DOI: 10.1007/s10058-024-00361-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10058-024-00361-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10058-024-00361-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    2. Hall, Robert E. & Kudlyak, Marianna, 2022. "The unemployed with jobs and without jobs," Labour Economics, Elsevier, vol. 79(C).
    3. Joshua S. Gans, 2022. "Test sensitivity for infection versus infectiousness of SARS‐CoV‐2," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(6), pages 1880-1887, September.
    4. Hunt Allcott & Levi Boxell & Jacob C. Conway & Billy A. Ferguson & Matthew Gentzkow & Benjamin Goldman, 2020. "What Explains Temporal and Geographic Variation in the Early US Coronavirus Pandemic?," NBER Working Papers 27965, National Bureau of Economic Research, Inc.
    5. Goolsbee, Austan & Syverson, Chad, 2021. "Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020," Journal of Public Economics, Elsevier, vol. 193(C).
    6. Neil M. Ferguson & Derek A. T. Cummings & Christophe Fraser & James C. Cajka & Philip C. Cooley & Donald S. Burke, 2006. "Strategies for mitigating an influenza pandemic," Nature, Nature, vol. 442(7101), pages 448-452, July.
    7. Glenn Ellison, 2020. "Implications of Heterogeneous SIR Models for Analyses of COVID-19," NBER Working Papers 27373, National Bureau of Economic Research, Inc.
    8. Ploutarchos Tzampoglou & Dimitrios Loukidis, 2020. "Investigation of the Importance of Climatic Factors in COVID-19 Worldwide Intensity," IJERPH, MDPI, vol. 17(21), pages 1-25, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. Bisin, Alberto & Moro, Andrea, 2022. "JUE insight: Learning epidemiology by doing: The empirical implications of a Spatial-SIR model with behavioral responses," Journal of Urban Economics, Elsevier, vol. 127(C).
    3. Janiak, Alexandre & Machado, Caio & Turén, Javier, 2021. "Covid-19 contagion, economic activity and business reopening protocols," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 264-284.
    4. de Mello-Sampayo, F.;, 2024. "Uncertainty in Healthcare Policy Decisions: An Epidemiological Real Options Approach to COVID-19 Lockdown Exits," Health, Econometrics and Data Group (HEDG) Working Papers 24/01, HEDG, c/o Department of Economics, University of York.
    5. Callaway, Brantly & Li, Tong, 2023. "Policy evaluation during a pandemic," Journal of Econometrics, Elsevier, vol. 236(1).
    6. Wright, Austin L. & Sonin, Konstantin & Driscoll, Jesse & Wilson, Jarnickae, 2020. "Poverty and economic dislocation reduce compliance with COVID-19 shelter-in-place protocols," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 544-554.
    7. Xiao Chen & Hanwei Huang & Jiandong Ju & Ruoyan Sun & Jialiang Zhang, 2022. "Endogenous cross-region human mobility and pandemics," CEP Discussion Papers dp1860, Centre for Economic Performance, LSE.
    8. 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).
    9. Bisin, Alberto & Moro, Andrea, 2022. "Spatial‐SIR with network structure and behavior: Lockdown rules and the Lucas critique," Journal of Economic Behavior & Organization, Elsevier, vol. 198(C), pages 370-388.
    10. Dirk Niepelt & Mart n Gonzalez-Eiras, 2020. "Optimally Controlling an Epidemic," Diskussionsschriften dp2019, Universitaet Bern, Departement Volkswirtschaft.
    11. Antonio Diez de los Rios, 2022. "A macroeconomic model of an epidemic with silent transmission and endogenous self‐isolation," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 581-625, February.
    12. Abel Brodeur & David Gray & Anik Islam & Suraiya Bhuiyan, 2021. "A literature review of the economics of COVID‐19," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1007-1044, September.
    13. Andrew G. Atkeson & Karen A. Kopecky & Tao Zha, 2024. "Four Stylized Facts About Covid‐19," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 65(1), pages 3-42, February.
    14. Granja, João & Makridis, Christos & Yannelis, Constantine & Zwick, Eric, 2022. "Did the paycheck protection program hit the target?," Journal of Financial Economics, Elsevier, vol. 145(3), pages 725-761.
    15. Korolev, Ivan, 2021. "Identification and estimation of the SEIRD epidemic model for COVID-19," Journal of Econometrics, Elsevier, vol. 220(1), pages 63-85.
    16. Yasushi Iwamoto, 2021. "Welfare economics of managing an epidemic: an exposition," The Japanese Economic Review, Springer, vol. 72(4), pages 537-579, October.
    17. Dizioli, Allan & Pinheiro, Roberto, 2021. "Information and inequality in the time of a pandemic," Journal of Economic Dynamics and Control, Elsevier, vol. 130(C).
    18. Forsythe, Eliza & Kahn, Lisa B. & Lange, Fabian & Wiczer, David, 2022. "Where have all the workers gone? Recalls, retirements, and reallocation in the COVID recovery," Labour Economics, Elsevier, vol. 78(C).
    19. Çakmaklı, Cem & Demiralp, Selva & Özcan, Şebnem Kalemli & Yeşiltaş, Sevcan & Yıldırım, Muhammed A., 2023. "COVID-19 and emerging markets: A SIR model, demand shocks and capital flows," Journal of International Economics, Elsevier, vol. 145(C).
    20. André, Keven R.A. & Arbex, Marcelo & Corrêa, Márcio V., 2023. "The economic implications of a network SIR-Macro model of epidemics," Economics Letters, Elsevier, vol. 225(C).

    More about this item

    Keywords

    Epidemiological models; Macroeconomics; Antigen testing;
    All these keywords.

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:reecde:v:28:y:2024:i:4:d:10.1007_s10058-024-00361-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.