SEIQCR传染病模型的构建及在广州市新型冠状病毒肺炎公共卫生防控效果评估中的应用

doi:10.6040/j.issn.1671-7554.0.2020.0775

摘要/Abstract

摘要： 目的构建易感者(S)-潜伏者(E)-发病者(I)-隔离者(Q)-确诊者(C)-恢复者(R)模型(SEIQCR),并初步用于评价广州市新型冠状病毒肺炎(COVID-19)疫情中公共卫生干预措施的效果。方法在SEIR传播动力学模型基础上,添加隔离模块和确诊模块,建立联合考虑潜伏期传播规律和追踪隔离干预措施的SEIQCR传播动力学模型。以2020年1月13日至2020年3月17日广州市疫情数据为基础,拟合得到SEIQCR模型的动力学参数。结果 SEIQCR模型显示预测每日发病数与实际发病数高度吻合(R2=0.93)。启动一级响应之后,时变再生数(R_t)呈快速下降趋势,提示本地传播得到有效控制。结论广州市COVID-19疫情的防控措施是有效的,各地方政府应严格执行隔离制度,切断传播途径,全力遏制COVID-19 传播。SEIQCR模型的构建策略可为其他地区的干预措施评估提供方法学借鉴。

关键词: 新型冠状病毒肺炎, 干预作用, 传染病动力学模型

Abstract: Objective To develop a dynamic model of susceptible(S), exposed people in the latent period(E), infective(I), quarantined(Q), confirmed(C), and recovered(R)(SEIQCR)to evaluate the role of interventions and control the coronavirus disease 2019(COVID-19)epidemic in Guangzhou. Methods Based on the SEIR propagation dynamics model, the modules of “quarantined” and “confirmed” cases were added to establish a new SEIQCR model. The epidemic data in Guangzhou from Jan. 13 to Mar. 17, 2020 were fitted to obtain the parameters of SEIQCR model. Results The number of predicted cases based on these parameters was highly consistent with the actual incidence(R2=0.93). Time-dependent reproduction number declined rapidly with the implementation of first level response to COVID-19, indicating that local transmission was effectively controlled. Conclusion The preventative and control measures were effective. Local government should continue strictly implementing the isolation system and cut off the transmission channels to curb the transmission of COVID-19. The SEIQCR model can provide methodological reference for intervention assessment in other regions.

Key words: Coronavirus disease 2019, Intervention effect, SEIQCR model

中图分类号:

R181.2

徐丽君, 刘文辉, 刘远, 李美霞, 罗雷, 欧春泉. SEIQCR传染病模型的构建及在广州市新型冠状病毒肺炎公共卫生防控效果评估中的应用[J]. 山东大学学报 (医学版), 2020, 58(10): 20-24.

XU Lijun, LIU Wenhui, LIU Yuan, LI Meixia, LUO Lei, OU Chunquan. Construction of SEIQCR epidemic model and its application in the evaluation of public health interventions on COVID-19 in Guangzhou[J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 20-24.

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