Journal of Geo-information Science ›› 2021, Vol. 23 ›› Issue (2): 259-273.doi: 10.12082/dqxxkx.2021.200356

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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)

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