Investigating the Evolution and Transmission of Emergencies in Large-Scale Events Using a Scenario-Based Representation Model

Abstract

Emergency often leads to a series of derivative and secondary emergencies during large-scale events, which can cause severe losses of human resources and property, as well as negative social effects. This study aims to clarify the evolution and transmission mechanism of emergencies using a new scenario-based representation model, which enables decision-makers to deal effectively with various types of emergencies and thus achieve the goals of reducing potential risks, minimizing unnecessary loss, and maintaining public security in large-scale events. Then, based on this model and using the 2022 Beijing Winter Olympics as an example, a hypothetical terrorist attack is proposed as the initial emergency to predict a network of subsequent emergencies. Furthermore, the rationality of the network built by the proposed model is verified by using the Bayesian network.