Modeling a Decision Support System for Risk Management of COVID-19

A decision support system that performs a comprehensive analysis on risks of the COVID-19 pandemic and its subsequent medium- and long-term impacts is highly desirable, especially in view of the still ongoing pandemic in the world. This paper focuses on the modeling process of such a decision support system. The modeling process includes the following steps: generating appropriate strategies that suit the specific situation concerned, where each strategy is composed of measures and each measure consists of a static (textual) part relating to the contexts abstracted from existing literature via techniques inspired by natural language processing and a dynamic part adapted by using scenario planning method and agent-based simulation; generating utility-based recommender based on soft systems methodology and recommending the Top-N strategies to the group of stakeholders based on the scores of the strategies using multiple-criteria decision analysis method. The proposed model is highly flexible in that it recommends appropriate strategies in respect of the various scenarios concerned and may thus be applied to various types of risk management.