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Modeling to Inform Economy-Wide Pandemic Policy: Bringing Epidemiologists and Economists Together

Author

Listed:
  • Michael E. Darden
  • David Dowdy
  • Lauren Gardner
  • Barton Hamilton
  • Karen Kopecky
  • Melissa Marx
  • Nicholas W. Papageorge
  • Daniel Polsky
  • Kimberly Powers
  • Elizabeth Stuart
  • Matthew Zahn

Abstract

Facing unprecedented uncertainty and drastic trade-offs between public health and other forms of human well-being, policy makers during the Covid-19 pandemic have sought the guidance of epidemiologists and economists. Unfortunately, while both groups of scientists use many of the same basic mathematical tools, the models they develop to inform policy tend to rely on different sets of assumptions and, thus, often lead to different policy conclusions. This divergence in policy recommendations can lead to uncertainty and confusion, opening the door to disinformation, distrust of institutions, and politicization of scientific facts. Unfortunately, to date, there have not been widespread efforts to build bridges and find consensus or even to clarify sources of differences across these fields, members of whom often continue to work within their traditional academic silos. In response to this “crisis of communication,” we convened a group of scholars from epidemiology, economics, and related fields (e.g., statistics, engineering, and health policy) to discuss approaches to modeling economy-wide pandemics. We summarize these conversations by providing a consensus view of disciplinary differences (including critiques) and working through a specific policy example. Thereafter, we chart a path forward for more effective synergy between disciplines, which we hope will lead to better policies as the current pandemic evolves and future pandemics emerge.

Suggested Citation

  • Michael E. Darden & David Dowdy & Lauren Gardner & Barton Hamilton & Karen Kopecky & Melissa Marx & Nicholas W. Papageorge & Daniel Polsky & Kimberly Powers & Elizabeth Stuart & Matthew Zahn, 2021. "Modeling to Inform Economy-Wide Pandemic Policy: Bringing Epidemiologists and Economists Together," NBER Working Papers 29475, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:29475
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    References listed on IDEAS

    as
    1. Seth G. Benzell & Avinash Collis & Christos Nicolaides, 2020. "Rationing social contact during the COVID-19 pandemic: Transmission risk and social benefits of US locations," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(26), pages 14642-14644, June.
    2. Michael E. Darden & David Dowdy & Lauren Gardner & Barton H. Hamilton & Karen Kopecky & Melissa Marx & Nicholas W. Papageorge & Daniel Polsky & Kimberly A. Powers & Elizabeth A. Stuart & Matthew V. Za, 2022. "Modeling to inform economy‐wide pandemic policy: Bringing epidemiologists and economists together," Health Economics, John Wiley & Sons, Ltd., vol. 31(7), pages 1291-1295, July.
    3. Lyndon P. James & Joshua A. Salomon & Caroline O. Buckee & Nicolas A. Menzies, 2021. "The Use and Misuse of Mathematical Modeling for Infectious Disease Policymaking: Lessons for the COVID-19 Pandemic," Medical Decision Making, , vol. 41(4), pages 379-385, May.
    4. Eleanor J. Murray, 2020. "Epidemiology's Time of Need: COVID-19 Calls for Epidemic-Related Economics," Journal of Economic Perspectives, American Economic Association, vol. 34(4), pages 105-120, Fall.
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    Cited by:

    1. Michael E. Darden & David Dowdy & Lauren Gardner & Barton H. Hamilton & Karen Kopecky & Melissa Marx & Nicholas W. Papageorge & Daniel Polsky & Kimberly A. Powers & Elizabeth A. Stuart & Matthew V. Za, 2022. "Modeling to inform economy‐wide pandemic policy: Bringing epidemiologists and economists together," Health Economics, John Wiley & Sons, Ltd., vol. 31(7), pages 1291-1295, July.
    2. Lorenzo Amir Nemati Fard & Michele Starnini & Michele Tizzoni, 2023. "Modeling adaptive forward-looking behavior in epidemics on networks," Papers 2301.04947, arXiv.org.

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    More about this item

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • H0 - Public Economics - - General
    • I1 - Health, Education, and Welfare - - Health
    • J0 - Labor and Demographic Economics - - General

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