地球信息科学学报 ›› 2021, Vol. 23 ›› Issue (2): 259-273.doi: 10.12082/dqxxkx.2021.200356

• 疫情建模与仿真 • 上一篇    下一篇

一种基于改进SEIR模型的突发公共卫生事件风险动态评估与预测方法——以欧洲十国COVID-19为例

毕佳(), 王贤敏*(), 胡跃译, 罗孟涵, 张俊华, 胡凤昌, 丁子洋   

  1. 中国地质大学(武汉) 地球物理与空间信息学院 地球内部多尺度成像湖北省重点实验室, 武汉 430074
  • 收稿日期:2020-07-08 修回日期:2020-11-13 出版日期:2021-02-25 发布日期:2021-04-25
  • 通讯作者: 王贤敏 E-mail:18839133121@163.com;xianminwang@163.com
  • 作者简介:毕 佳(1997— ),女,河南南阳人,硕士生,主要研究方向为数据挖掘与机器学习、地球空间信息技术。E-mail: 18839133121@163.com
  • 基金资助:
    国家自然科学基金项目(41372341);中央高校基本科研业务费项目(CUG2018JM09)

A Method for Dynamic Risk Assessment and Prediction of Public Health Emergencies based on an Improved SEIR Model: Novel Coronavirus COVID-19 in Ten European Countries

BI Jia(), WANG Xianmin*(), HU Yueyi, LUO Menghan, ZHANG Junhua, HU Fengchang, DING Ziyang   

  1. Hubei Subsurface Multi-scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China
  • Received:2020-07-08 Revised:2020-11-13 Online:2021-02-25 Published:2021-04-25
  • Contact: WANG Xianmin E-mail:18839133121@163.com;xianminwang@163.com
  • Supported by:
    National Natural Science Foundation of China(41372341);The Fundamental Research Funds for the Central Universities(CUG2018JM09)

摘要:

突发公共卫生事件会严重影响社会公众生命健康,风险评估和预测可为突发公共卫生事件有效防控提供科学依据。本文提出了一种基于SEIR模型的突发公共卫生事件风险动态评估与预测方法,将突发公共卫生事件传播与人口、医疗、经济情况相结合,耦合危险性与脆弱性,建立合理的风险评估综合指标体系,利用熵值—层次分析组合模型实现突发公共卫生事件风险动态评估。此外,本文建立了传染病传播动力学修正SEIR模型,将传染病传播动力学模拟预测与风险评估相结合,实现突发公共卫生事件演变趋势的预测和风险的动态预测。2019年12月底的COVID-19疫情是一次传播速度快、感染范围广、防控难度大的重大突发公共卫生事件。本文以欧洲10国COVID-19疫情为例,开展风险评估与风险动态预测研究,依据欧洲10国自疫情开始至2020年4月16日的疫情数据,预测了2020年4月17日—2020年5月10日疫情演变的趋势,进而实现了10国的疫情风险动态预测。本文模型预测结果表明至2020年5月10日欧洲10国疫情形势仍然严峻,预测数据与真实数据的拟合优度R 2大于0.92,预测结果与疫情真实情况基本一致,在此情况下,复工复产对于疫情防控仍然是不利的。本文提出的基于SEIR模型的公共卫生事件风险动态评估与预测方法为疫情已然传播开的国家和地区提供了风险持续评估和预测的可能,为后期疫情防控决策提供了支持,同时也可用于今后新的疫情发生时期或其他突发性公共卫生事件下风险的应急评估和预测。

关键词: 突发公共卫生事件, 风险评估, 风险预测, SEIR模型, COVID-19

Abstract:

Public health emergencies can seriously affect public health and people's lives, and risk assessment and prediction provide a scientific basis for effective prevention and control of public health emergencies. This work proposes a new method for risk dynamic assessment and prediction of public health emergencies based on a revised SEIR model. This work combines transmission rules of public health emergencies with demographic, medical, and economic conditions and establishes rational and comprehensive indices of risk assessment by coupling hazard evaluation and vulnerability estimation. An integrated model of entropy-AHP is employed to implement risk dynamic assessments of public health emergencies. Moreover, this work establishes a modified SEIR model and combines infectious disease transmission dynamics and risk assessment to predict evolutional trends and dynamic risks. The COVID-19 epidemic at the end of December 2019 was an important public health emergency characterized by rapid spread, widespread infection, and great difficulty in prevention and control. The COVID-19 epidemic in 10 European countries is employed as a case study for risk assessment and dynamic prediction. Based on the epidemic data from the beginning to April 16, 2020, the epidemic evolutionary trends and dynamic risks are predicted in these countries from April 17, 2020 to May 10, 2020. According to the prediction results, the epidemic situation in 10 European countries will be severe by May 10, 2020. The goodness of fit R2 is larger than 0.92, and the prediction results are basically consistent with the real epidemic situation. Work resumption will be unfavorable for epidemic prevention and control in this case. The method proposed in this work may offer continuous epidemic risk assessments and predictions for countries and regions with serious outbreaks, support effective decisions for disease prevention and control, and also provide emergency risk evaluations and predictions in new epidemic outbreak periods and for other public security emergencies in the future.

Key words: public health emergency, risk assessment, risk prediction, SEIR model, COVID-19