IDEAS home Printed from https://ideas.repec.org/a/aea/apandp/v111y2021p356-60.html

Behavior and the Transmission of COVID-19

Author

Listed:
  • Andrew G. Atkeson
  • Karen Kopecky
  • Tao Zha

Abstract

A simple model of COVID-19 that incorporates feedback from disease prevalence to disease transmission through an endogenous response of human behavior does a remarkable job fitting the main features of the data on the growth rates of daily deaths observed across a large number of countries and states in the United States in 2020. This finding, however, suggests a new empirical puzzle: very large wedges that shift disease transmission rates holding disease prevalence fixed are required both across regions and within a region over time for the model to match the data on deaths from COVID-19 as an equilibrium outcome exactly.

Suggested Citation

  • Andrew G. Atkeson & Karen Kopecky & Tao Zha, 2021. "Behavior and the Transmission of COVID-19," AEA Papers and Proceedings, American Economic Association, vol. 111, pages 356-360, May.
    • Handle: RePEc:aea:apandp:v:111:y:2021:p:356-60
    DOI: 10.1257/pandp.20211064
    as

    Download full text from publisher

    File URL: https://www.aeaweb.org/doi/10.1257/pandp.20211064
    Download Restriction: no
    File URL: https://www.aeaweb.org/doi/10.1257/pandp.20211064.ds
    Download Restriction: Access to full text is restricted to AEA members and institutional subscribers.
    File URL: https://libkey.io/10.1257/pandp.20211064?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
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Stefan Pollinger, 2023. "Optimal Contact Tracing and Social Distancing Policies to Suppress A New Infectious Disease," The Economic Journal, Royal Economic Society, vol. 133(654), pages 2483-2503.
    2. Hsu, Wen-Tai & Lin, Hsuan-Chih (Luke) & Yang, Han, 2023. "Between lives and economy: COVID-19 containment policy in open economies," European Economic Review, Elsevier, vol. 157(C).
    3. Eichenbaum, Martin S. & Rebelo, Sergio & Trabandt, Mathias, 2022. "The macroeconomics of testing and quarantining," Journal of Economic Dynamics and Control, Elsevier, vol. 138(C).
    4. Brooks, Wyatt & Donovan, Kevin & Johnson, Terence R. & Oluoch-Aridi, Jackline, 2022. "Cash transfers as a response to COVID-19: Experimental evidence from Kenya," Journal of Development Economics, Elsevier, vol. 158(C).
    5. Emiliozzi, Simone & Rondinelli, Concetta & Villa, Stefania, 2025. "Unveiling consumption patterns during COVID-19: Insights from credit cards," Economic Modelling, Elsevier, vol. 147(C).
    6. Matthew Goodkin-Gold & Michael Kremer & Christopher M. Snyder & Heidi Williams, 2024. "Optimal Vaccine Subsidies for Epidemic Diseases," The Review of Economics and Statistics, MIT Press, vol. 106(4), pages 895-909, July.
    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. Lin Ma & Gil Shapira & Damien de Walque & Quy‐Toan Do & Jed Friedman & Andrei A. Levchenko, 2022. "The Intergenerational Mortality Trade‐Off Of Covid‐19 Lockdown Policies," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(3), pages 1427-1468, August.
    9. Carnehl, Christoph & Fukuda, Satoshi & Kos, Nenad, 2023. "Epidemics with behavior," Journal of Economic Theory, Elsevier, vol. 207(C).
    10. Yinon Bar-On & Tatiana Baron & Ofer Cornfeld & Eran Yashiv, 2023. "When to Lock, Not Whom: Managing Epidemics Using Time-Based Restrictions," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 51, pages 292-321, December.
    11. Paul Ho, 2021. "Forecasting in the Absence of Precedent," Working Paper 21-10, Federal Reserve Bank of Richmond.
    12. Proaño, Christian R. & Kukacka, Jiri & Makarewicz, Tomasz, 2024. "Belief-driven dynamics in a behavioral SEIRD macroeconomic model with sceptics," Journal of Economic Behavior & Organization, Elsevier, vol. 217(C), pages 312-333.
    13. Deiana, Claudio & Geraci, Andrea & Mastrobuoni, Giovanni & Weidenholzer, Simon, 2025. "Running the risk: Immunity and mobility in response to a pandemic," European Economic Review, Elsevier, vol. 177(C).

    More about this item

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

    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:aea:apandp:v:111:y:2021:p:356-60. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Michael P. Albert (email available below). General contact details of provider: https://edirc.repec.org/data/aeaaaea.html .

    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.