Print Email Facebook Twitter Decision making under deep uncertainty for pandemic policy planning Title Decision making under deep uncertainty for pandemic policy planning Author Hadjisotiriou, Sophie (Radboud University Medical Center) Marchau, V.A.W.J. (Radboud Universiteit Nijmegen) Walker, W.E. (TU Delft Air Transport & Operations) Rikkert, Marcel Olde (Radboud University Medical Center) Date 2023 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. Subject COVID-19PolicymakingReliable organizationsSystems analysisUncertainty To reference this document use: http://resolver.tudelft.nl/uuid:420dd843-6e25-4f18-8b62-7b86c13de878 DOI https://doi.org/10.1016/j.healthpol.2023.104831 ISSN 0168-8510 Source Health Policy, 133 Part of collection Institutional Repository Document type journal article Rights © 2023 Sophie Hadjisotiriou, V.A.W.J. Marchau, W.E. Walker, Marcel Olde Rikkert Files PDF 1_s2.0_S0168851023001161_main.pdf 969.69 KB Close viewer /islandora/object/uuid:420dd843-6e25-4f18-8b62-7b86c13de878/datastream/OBJ/view