Decision making under deep uncertainty for pandemic policy planning
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Published on: September 16, 2015
Sophie Hadjisotiriou1, Vincent Marchau2, Warren Walker3
1Radboud UMC, Faculty of Medical Sciences, Reinier Postlaan 4, 6525 GC Nijmegen, the Netherlands.
Abstract:
Policymakers around the world were generally unprepared for the global COVID-19 pandemic. As a result, the virus has led to millions of cases and hundreds of thousands of deaths. Theoretically, the number of cases and deaths did not have to happen (as demonstrated by the results in a few countries). In this pandemic, as in other great disasters, policymakers are confronted with what policy analysts call Decision Making under Deep Uncertainty (DMDU). Deep uncertainty requires policies that are not based on 'predict and act' but on 'prepare, monitor, and adapt', enabling policy adaptations over time as events occur and knowledge is gained. We discuss the potential of a DMDU-approach for pandemic decisionmaking.
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