突发公共卫生事件衍生社会风险预警与防范的实证分析

Empirical Analysis on Early Warning and Prevention of Derivative Social Risks From Public Health Emergency

基于突发公共卫生事件下衍生社会风险的监测数据信息,用来建立风险评估与预警模型进行衍生社会风险等级的快速识别,用来提高相关负责部门对衍生社会风险的监测水平和应对能力。收集了107起典型突发公共卫生事件案例,利用多维情景空间分析法构建包含社会生理、社会心理、社会行为、社会应对以及社会环境风险五个维度的衍生社会风险评估指标体系,进而基于指标量化规则对案例的衍生社会风险评估指标进行量化打分,最后利用熵权—TOPSIS方法构建衍生社会风险评估及预警模型,通过测算最终将风险等级划分为轻度、中度、重度、和特度警情四个等级。

Based on the monitoring data of derivative social risks in public health emergencies,a risk assessment and early warning model is constructed to quickly identify the level of derivative social risks,so as to improve the monitoring level and response ability of the relevant responsible departments to derivative social risks.we collected 107 cases of typical public health emergencies,constructed a derivative social risk assessment index system including social physiology,social psychology,social behavior,social coping and social environmental risk by using the method of multi-dimensional situational spatial analysis,and then quantitatively scored the derivative social risk assessment indicators of the case based on the quantitative rules of the index.Finally,the entropy weight-TOPSIS method is used to build a derivative social risk assessment and early warning model.Through calculation,the risk level is divided into four levels:mild,moderate,severe,and special warning.