基于ERMM的新冠病毒疫情分级与动态预警研究  

Research on the classification and dynamic warning of COVID-19 epidemic based on ERMM

作　　者：刘玉成[1,2] 王传生 杨露鑫[3] LIU Yucheng;WANG Chuansheng;YANG Luxin(State Key Laboratory,Nanjing University of Finance and Economics,Nanjing 210023,China;School of Management and Engineering,Capital University of Economics and Business,Beijing 100070,China;Institute of International Economy,University of International Business and Economics,Beijing 100029,China)

机构地区：[1]南京财经大学国家重点实验室,江苏南京210023 [2]首都经济贸易大学管理工程学院,北京100070 [3]对外经济贸易大学国际经济研究院,北京100029

出　　处：《管理工程学报》2023年第4期99-113,共15页Journal of Industrial Engineering and Engineering Management

基　　金：国家自然科学基金资助青年项目(71702068);北京社会科学基金资助项目(20GLB028);北京市自然科学基金资助项目(9192005)。

摘　　要：新冠疫情的精准判定是打赢疫情防控阻击战的金钥匙,而精准的疫情防控则是经济社会高质量发展和如期打赢脱贫攻坚战的压舱石。为精准判定区域单元的疫情风险和预警等级,基于泛逻辑模糊集与模糊数学等知识理论,创新性地构建了疫情风险计量模型(epidemic risk measurement model,ERMM)及其子模块的计量模型。本文通过采集“人口迁移”“外环境”“防疫重视程度”和“病理学”等四个维度的样本数据,并采用ERMM1等不同的方法,对预警区域各子模块进行计量运算;并根据各子模块的运算结果,运用ERMM对预警区域进行统一的合成运算;同时对不同区域单元的新冠病毒疫情进行多层面的仿真研究与深度分析。研究结果表明:(1)ERMM的一级指标和二级指标对新冠疫情的影响作用均非常显著。且三者之间存在线性和非线性关系共存的复杂逻辑关系。二级指标的作用通过一级指标传导,两者共同决定着区域单元的新冠病毒疫情程度。(2)预警区域普遍存在总体预警等级合理,但局部预警等级设置不准确的现象;从而导致局部防疫反应过度或针对性不强等不同的状况。(3)ERMM能够准确判定区域单元的疫情风险和预警等级,进而可为新冠疫情的准确预警、科学防控及精准施策而赋能赋智。Accurate determination of COVID-19 epidemic is the essential to win the fight against the epidemic,and accurate prevention and control of the epidemic is the core initiatives for high-quality economic and social development and the fight against poverty as planned.In order to accurately determine the epidemic risk and warning degree of regional units,based on theoretical knowledge such as pan-logic fuzzy sets and fuzzy mathematics,it innovatively constructed an epidemic risk measurement model(ERMM)and its sub-module measurement models.The ERMM epidemic risk measurement model constructed in this article not only considered the“the public′s travel intensity and contact intensity”,“the security of the external activity environment”,“the public′s vigilance against the epidemic prevention”and“the basic scale of the regional original cases”that determine the severity of the epidemic,also considered the comprehensive and in-depth analysis from endogenous and external variables,and took into account the influence of“hard”factors such as cases and“soft”factors such as the public′s attention.The ERMM model is based on the basic theories of multiple disciplines such as pan-logic fuzzy sets,fuzzy mathematics,computer logic,and engineering mathematics.Besides,the modules are respectively innovated and improved,so that the ERMM model can accurately consider and judge the situation of the COVID-19 pneumonia nationwide and even the world from the four dimensions of“population migration”,“external environment”,“epidemic prevention emphasis”and“pathology”.Then find out the inherent characteristics and essential laws of the global COVID-19 pneumonia epidemic.Finally,it can help to explore the precise strategies and effective ways of epidemiological investigation and source tracing of the global COVID-19 pneumonia epidemic.First of all,this article integrated the four sub-measurement models of population migration module(ERMM1l),external environment module(ERMM2l),epidemic prevention emp

关 键 词：新冠疫情 动态预警 ERMM模型 多层面计量 逻辑关系 

分 类 号：F407[经济管理—产业经济]