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Building a Bayesian decision support system for evaluating COVID-19 countermeasure strategies

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Listed:
  • Strong, Peter
  • Shenvi, Aditi
  • Yu, Xuewen
  • Papamichail, K. Nadia
  • Wynn, Henry P.
  • Smith, Jim Q.

Abstract

Decision making in the face of a disaster requires the consideration of several complex factors. In such cases, Bayesian multi-criteria decision analysis provides a framework for decision making. In this paper, we present how to construct a multi-attribute decision support system for choosing between countermeasure strategies, such as lockdowns, designed to mitigate the effects of COVID-19. Such an analysis can evaluate both the short term and long term efficacy of various candidate countermeasures. The expected utility scores of a countermeasure strategy capture the expected impact of the policies on health outcomes and other measures of population well-being. The broad methodologies we use here have been established for some time. However, this application has many novel elements to it: the pervasive uncertainty of the science; the necessary dynamic shifts between regimes within each candidate suite of countermeasures; and the fast moving stochastic development of the underlying threat all present new challenges to this domain. Our methodology is illustrated by demonstrating in a simplified example how the efficacy of various strategies can be formally compared through balancing impacts of countermeasures, not only on the short term (e.g. COVID-19 deaths) but the medium to long term effects on the population (e.g. increased poverty).

Suggested Citation

  • Strong, Peter & Shenvi, Aditi & Yu, Xuewen & Papamichail, K. Nadia & Wynn, Henry P. & Smith, Jim Q., 2023. "Building a Bayesian decision support system for evaluating COVID-19 countermeasure strategies," LSE Research Online Documents on Economics 113632, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:113632
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    File URL: http://eprints.lse.ac.uk/113632/
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    References listed on IDEAS

    as
    1. John D. W. Morecroft, 1984. "Strategy support models," Strategic Management Journal, Wiley Blackwell, vol. 5(3), pages 215-229, July.
    2. Jonathan Karnon, 2020. "A Simple Decision Analysis of a Mandatory Lockdown Response to the COVID-19 Pandemic," Applied Health Economics and Health Policy, Springer, vol. 18(3), pages 329-331, June.
    3. Geldermann, Jutta & Bertsch, Valentin & Treitz, Martin & French, Simon & Papamichail, Konstantinia N. & Hämäläinen, Raimo P., 2009. "Multi-criteria decision support and evaluation of strategies for nuclear remediation management," Omega, Elsevier, vol. 37(1), pages 238-251, February.
    4. Layard, Richard & Clark, Andrew E. & De Neve, Jan-Emmanuel & Krekel, Christian & Fancourt, Daisy & Hey, Nancy & O'Donnell, Gus, 2020. "When to release the lockdown: a wellbeing framework for analysing costs and benefits," LSE Research Online Documents on Economics 104276, London School of Economics and Political Science, LSE Library.
    5. Layard, Richard & Clark, Andrew E. & De Neve, Jan-Emmanuel & Krekel, Christian & Fancourt, Daisy & Hey, Nancy & O'Donnell, Gus, 2020. "When to release the lockdown: a wellbeing framework for analysing costs and benefits," LSE Research Online Documents on Economics 104276, London School of Economics and Political Science, LSE Library.
    6. Erik P Vargo & Randy Cogill, 2015. "Expectation-maximization for Bayes-adaptive POMDPs," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(10), pages 1605-1623, October.
    7. Margaret H. Kurth & Sabrina Larkin & Jeffrey M. Keisler & Igor Linkov, 2017. "Trends and applications of multi-criteria decision analysis: use in government agencies," Environment Systems and Decisions, Springer, vol. 37(2), pages 134-143, June.
    8. J Moffat & S Witty, 2002. "Bayesian decision making and military command and control," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(7), pages 709-718, July.
    9. Keeney,Ralph L. & Raiffa,Howard, 1993. "Decisions with Multiple Objectives," Cambridge Books, Cambridge University Press, number 9780521438834, October.
    10. Jan-Emmanuel de Neve & Andrew E. Clark & Christian Krekel & Richard Layard & Gus O’donnell, 2020. "Taking a wellbeing years approach to policy choice," PSE-Ecole d'économie de Paris (Postprint) halshs-02973078, HAL.
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    More about this item

    Keywords

    Covid-19; decision support system; expected utility; emergency management; multi-criteria; evaluation methodology; coronavirus;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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