SEIAR传染病动力学模型的建立及实现  

Establishment and application of SEIAR model

作　　者：刘天[1,2] 赵泽宇 姚梦雷 黄继贵[1] 梅芳盛[1] 陈田木[3] Liu Tian;Zhao Zeyu;Yao Menglei;Huang Jigui;Mei Fangsheng;Chen Tianmu(Department for Infectious Disease Control and Prevention,Jingzhou Prefectural Center for Disease Control and Prevention,Jingzhou 434000,Hubei,China;Chinese Field Epidemiology Training Program,Beijing 100050,China;State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics,School of Public Health,Xiamen University,Xiamen 361102,Fujian,China)

机构地区：[1]荆州市疾病预防控制中心传染病防治所,湖北荆州434000 [2]中国现场流行病学培训项目,北京100050 [3]厦门大学公共卫生学院分子疫苗学与分子诊断学国家重点实验室,福建厦门361102

出　　处：《疾病监测》2020年第10期934-938,共5页Disease Surveillance

摘　　要：目的利用Berkeley Madonna软件建立SEIAR模型,梳理建模步骤及代码。方法收集荆州市一起流感暴发疫情病例发病时间资料,利用Berkeley Madonna软件分别建立无干预措施的模型(SEIAR0)、采取病例隔离控制措施的模型(SEIAR_I)、采取班级停课的模型(SEIAR_C)和同时采取两种干预措施的模型(SEIAR_M)。选择累计罹患率(TAR)和疫情持续时间(DO)比较采取干预措施对暴发疫情的影响。模型参数β经曲线拟合获得,余参数参考同类研究并进行敏感性分析。结果该起疫情自2017年11月12日出现病例,11月17日、21日分别采取病例隔离和班级停课的控制措施。参数β最优值为0.00105,SEIAR0模型的TAR为85.90%,DO为49 d。SEIAR_M、SEIAR_I、SEIAR_C较SEIAR0的TAR分别下降95.25%、89.94%和73.32%;DO依次为29 d、78 d和39 d。敏感性分析结果显示,参数变化时,TAR介于71.42%~86.02%。结论Berkeley Madonna软件建立SEIAR模型简单、易行,适于评价干预措施的效果。Objective To establish a SEIAR model by using software Berkeley Madonna and analyze the modeling steps and code.Methods Data on the onset time of an influenza outbreak in a city were collected.The Berkeley Madonna software was used to establish a non-intervention model(SEIAR0),a model for case isolation(SEIAR_I),a model for class suspension(SEIAR_C),and a model for comprehensive intervention(SEIAR_M).The cumulative attack rate(TAR)and duration of epidemics(DO)were used to compare the impact of interventions on outbreaks.The parameterβof the model was obtained by curve fitting,and other parameters were based on the same kind of research and sensitivity analysis on the stability of the result.Results The influenza epidemic occurred on November 12,2017,and the control measures for case isolation and class suspension were taken on November 17 and November 21 respectively.The optimal value ofβwas 0.00105,the TAR of the SEIAR0 model was 85.90%,and the DO was 49 days.SEIAR_M,SEIAR_I,and SEIAR_C decreased by 95.25%,89.94%,and73.32%,respectively,compared with SEIAR0.DO was 29 days,78 days,and 39 days,respectively.The sensitivity analysis showed that the TAR was between 71.42%and 86.02%when the parameters changed.Conclusion The SEIAR model established with Berkeley Madonna software is simple and easy to use,which is suitable for the evaluation of intervention effects.

关 键 词：易感者-潜伏期-显性/隐性感染者-移出者 暴发 流行性感冒 数学建模 Berkeley Madonna软件 

分 类 号：R211[医药卫生—中医学] R512.5