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

Strong, Peter, Shenvi, Aditi, Yu, Xuewen, Papamichail, K. Nadia, Wynn, Henry P. ORCID: 0000-0002-6448-1080 and Smith, Jim Q. (2023) Building a Bayesian decision support system for evaluating COVID-19 countermeasure strategies. Journal of the Operational Research Society, 74 (2). 476 - 488. ISSN 0160-5682

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Identification Number: 10.1080/01605682.2021.2023673

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).

Item Type: Article
Official URL: https://www.tandfonline.com/journals/tjor20
Additional Information: © 2022 The Authors
Divisions: Statistics
Subjects: H Social Sciences > HA Statistics
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
H Social Sciences > HV Social pathology. Social and public welfare. Criminology
Date Deposited: 04 Feb 2022 15:15
Last Modified: 22 Mar 2024 20:00
URI: http://eprints.lse.ac.uk/id/eprint/113632

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