A risk-based decision framework for policy analysis of societal pandemic effects.

Introduction: In this article, we summarize 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. Methods: 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. We used the computer-supported tool DecideIT for the aggregate decision analysis under uncertainty. Results: The framework has been applied in three countries: Botswana, Romania and Jordan, and extended for scenario-building during the third wave of the pandemic in Sweden, proving its feasibility in real-time policy-making for pandemic mitigation measures. Discussion: This work resulted in a more fine-grained model for policy decision that is much more aligned to the societal needs in the future, either if the Covid-19 pandemic prevails or for the next pandemic or other society-wide hazardous emergencies.

A Multicriteria Approach to Modelling Pandemic Response under Strong Uncertainty: A Case Study in Jordan

In responding to the COVID-19 pandemic, evidence-based policymaking and risk mitigation have been confronted with limited decision-making mechanisms under conditions of increased uncertainty. Such methods are particularly called for in contexts where reliable data to a large extent are missing and where the chosen policy would impact a variety of sectors. In this paper, we present an application of an integrated decision-making framework under ambiguity on how to contain the COVID-19 virus spread from a national policy point of view. The framework was applied in Jordan and considered both local epidemiologic and socioeconomic estimates in a multistakeholder multicriteria context. In particular, the cocreation process for eliciting attitudes, perceptions, and preferences amongst relevant stakeholder groups has often been missing from policy response to the pandemic, even though the containment measures’efficiency largely depends on their acceptance by the impacted groups. For this, there exist several methods attempting to elicit criteria weights, values, and probabilities ranging from direct rating and point allocation methods to more elaborated ones. To facilitate the elicitation, some of the approaches utilise elicitation methods whereby prospects are ranked using ordinal importance information, while others use cardinal information. Methods are sometimes assessed in case studies or more formally by utilising systematic simulations. Furthermore, the treatment of corresponding methods for the handling of the alternative’s values has sometimes been neglected. We demonstrate in our paper an approach for cardinal ranking in policy decision making in combination with imprecise or incomplete information concerning probabilities, weights, and consequences or alternative values. The results of our cocreation process are aggregated in the evaluation of alternative mitigation measures for Jordan, showcasing how a multistakeholder multicriteria decision mechanism can be employed in current or future challenges of pandemic situations, to facilitate management and mitigation of similar crises in the future, in any region.

A Multi-Criteria Framework for Pandemic Response Measures.

In managing the COVID-19 pandemic, several compelling narratives seem to have played a significant role in the decision-making processes regarding which risk mitigation and management measures to implement. Many countries were to a large extent unprepared for such a situation, even though predictions about a significant probability for a pandemic to occur existed, and national governments of several countries often acted in an uncoordinated manner, which resulted in many inconsistencies in the disaster risk reduction processes. Limited evidence has also made room for strategic narratives meant to persuade the public of the chosen set of actions, even though the degree of uncertainty regarding the outcomes of these was high, further complicating the situation. In this article, we assume a normative standpoint regarding rhapsodic decision making and suggest an integrated framework for a more elaborated decision analysis under the ambiguity of how to contain the virus spread from a policy point of view, while considering epidemiologic estimations and socioeconomic factors in a multi-stakeholder-multi-criteria context based on a co-creative work process for eliciting attitudes, perceptions, as well as preferences amongst relevant stakeholder groups. The framework, applied in our paper on Romania for demonstrative purposes, is used for evaluating mitigation measures for catastrophic events such as the COVID-19 situation, to mobilize better response strategies for future scenarios related to pandemics and other hazardous events, as well as to structure the production and analysis of narratives on the current pandemic effects.