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基于社会分工的流行病动力学建模与仿真研究
引用本文:李海滨.基于社会分工的流行病动力学建模与仿真研究[J].系统仿真学报,2020,32(5):745-758.
作者姓名:李海滨
作者单位:1. 内蒙古工业大学工程训练教学部,内蒙古 呼和浩特 010051; 2. 内蒙古自治区生命数据统计分析理论与神经网络建模重点实验室,内蒙古工业大学理学院,内蒙古 呼和浩特 010051
基金项目:国家自然科学基金(11962021)
摘    要:疫情预测是流行病防控体系中的重要一环,准确建立流行病演化动力学模型具有十分重要的意义。针对现有流行病建模方法中鲜有考虑群体中的社会分工问题,拟将整个群体划分为普通居民、社会服务人员和一线医务工作人员等三个子群,基于异质均匀混合理论,利用子群邻接矩阵表示个体间的接触关系,建立了流行病传播与演化的延时动力学模型。仿真结果表明,本文方法更符合实际情况,可为流行病动力学建模与仿真提供一种有效手段,对武汉疫情做了动力学建模与仿真分析。

关 键 词:流行病  建模  社会分工  邻接矩阵  新型冠状病毒-2019  
收稿时间:2020-03-19

Modeling and Simulation on Dynamics of Epidemic Disease Based on Social Division of Labor
Li haibin.Modeling and Simulation on Dynamics of Epidemic Disease Based on Social Division of Labor[J].Journal of System Simulation,2020,32(5):745-758.
Authors:Li haibin
Institution:1. Engineering Training Center of Inner Mongolia University of Technology, Hohhot 010051, China; 2. Inner Mongolia Key Laboratory of Statistical Analysis Theory for Life Data and Neural Network Modeling, College of Sciences, Inner Mongolia University of Technology, Hohhot 010051, China
Abstract:Prediction is an essential part of the epidemic prevention and control system, and it is of great significance to accurately establish a dynamic model of epidemiological evolution. The existing epidemiological modeling methods rarely consider the social division of labor of different groups. The entire group is divided into three subgroups, the ordinary residents, the social service personnel, and the front-line medical workers. Based on the heterogeneous uniform mixing theory, the subgroup adjacency matrix is used to represent the contact relationship between individuals, and a time-lapse dynamic model of epidemic spread and evolution is established. The simulation results show that this method is in line with the actual situation and can provide an effective method to the modeling and simulation of the epidemiological dynamics. The method carries out the dynamic modeling and simulation analysis of the epidemic situation in Wuhan.
Keywords:epidemic disease  modeling  social division of labor  adjacency matrix  COVID-19(Corona Virus Disease-2019)  
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