The significance of robust uncertainty quantification due to the incomplete knowledge in policymaking has been emphasized by many studies, particularly during a pandemic caused by a novel virus. However, current approaches are not designed to handle situations that are characterized by a complete lack of data. This project aims to assist policymakers by developing a decision-making framework for identifying the optimal pandemic response, given varying degrees of data availability. We will compare the actual decisions made by the Swiss policymakers against the optimal decisions recommended by our decision-making framework, given the level of uncertainty in the data during the different stages of COVID-19 pandemics.
