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19th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2022 ; 1601 CCIS:34-46, 2022.
Article in English | Scopus | ID: covidwho-1971507

ABSTRACT

Complex situations such as pandemics generally lead to consider different sources of information in the analysis. We propose a general framework for coronavirus risk assessment based on multi-criteria decision aiding (MCDA) where input variables are indicators expressed on the basis of qualitative-ordinal scales. The proposed approach, based on Sugeno Utility Functionals, makes the problem setting easy to interpret and allows us to reflect the policy-makers’ opinions on the importance of each indicator or subset of indicators. Interestingly, our approach is related to if-then rule-based systems adopted by some Governments for pandemic risk assessment and restriction policy planning. © 2022, Springer Nature Switzerland AG.

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