Decision making under deep uncertainty for pandemic policy planning

Sophie Hadjisotiriou, Vincent Marchau*, Warren Walker, Marcel Olde Rikkert

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
49 Downloads (Pure)


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.
Original languageEnglish
Article number104831
JournalHealth Policy
Publication statusPublished - 2023


  • COVID-19
  • Policymaking
  • Reliable organizations
  • Systems analysis
  • Uncertainty


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