A risk-based decision framework for policy analysis of societal pandemic effects - Danielson, Mats; Ekenberg, Love; Komendantova, Nadejda; Mihai, Adriana (Frontiers in Public Health, 2023)
In this article, we summarise our findings from an EU-supported project for policy analyses applied to pandemics such as Covid-19 (with the potential to be applied as well to other, similar hazards) while considering various mitigation levels and consequence sets under several criteria. It is based on our former development for handling imprecise information in risk trees and multi-criteria hierarchies using intervals and qualitative estimates. We shortly present the theoretical background and demonstrate how it can be used for systematic policy analyses. In our model, we use decision trees and multi-criteria hierarchies extended by belief distributions for weights, probabilities and values as well as combination rules to aggregate the background information in an extended expected value model, taking into criteria weights as well as probabilities and outcome values. The framework has been applied in three countries: Botswana, Romania and Jordan, where we also used the computer-supported tool DecideIT for this aggregate decision analysis under uncertainty.