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

Author

Listed:
  • Darden, Michael E.

    (The Johns Hopkins Carey Business School)

  • Dowdy, David

    (Johns Hopkins University)

  • Gardner, Lauren

    (Johns Hopkins University)

  • Hamilton, Barton H.

    (Washington University, St. Louis)

  • Kopecky, Karen A.

    (Federal Reserve Bank of Atlanta)

  • Marx, Melissa

    (Johns Hopkins University)

  • Papageorge, Nicholas W.

    (Johns Hopkins University)

  • Polsky, Daniel

    (Johns Hopkins University)

  • Powers, Kimberly

    (North Carolina State University)

  • Stuart, Elizabeth

    (Johns Hopkins University)

  • Zahn, Matthew V.

    (Johns Hopkins University)

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

  • Darden, Michael E. & Dowdy, David & Gardner, Lauren & Hamilton, Barton H. & Kopecky, Karen A. & Marx, Melissa & Papageorge, Nicholas W. & Polsky, Daniel & Powers, Kimberly & Stuart, Elizabeth & Zahn, , 2021. "Modeling to Inform Economy-Wide Pandemic Policy: Bringing Epidemiologists and Economists Together," IZA Discussion Papers 14838, IZA Network @ LISER.
  • Handle: RePEc:iza:izadps:dp14838
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    Cited by:

    1. Nemati Fard, Lorenzo Amir & Bisin, Alberto & Starnini, Michele & Tizzoni, Michele, 2025. "Modeling adaptive forward-looking behavior in epidemics on networks," Journal of Economic Behavior & Organization, Elsevier, vol. 232(C).
    2. Lorenzo Amir Nemati Fard & Alberto Bisin & Michele Starnini & Michele Tizzoni, 2023. "Modeling adaptive forward-looking behavior in epidemics on networks," Papers 2301.04947, arXiv.org, revised Jan 2025.
    3. 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.

    More about this item

    Keywords

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    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
    • J - Labor and Demographic Economics

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