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J Zhejiang Univ (Med Sci)  2021, Vol. 50 Issue (1): 41-51    DOI: 10.3724/zdxbyxb-2021-0035
    
Exploring early prevention and control of COVID-19 outbreak based on system dynamics model analysis
DONG Shi1(),CUI Zhiwei2,*(),PAN Xiaoxiong2,WANG Jianwei1,GAO Chao1
1. College of Transportation Engineering,Chang’an University,Xi’an 710064,China;
2. School of Economics and Management,Chang’an University,Xi’an 710064,China
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Abstract  

Objective: To explore early prevention and control of coronavirus disease 2019 (COVID-19) outbreak based on system dynamics model analysis. Methods:The data of early outbreak of COVID-19 were collected from the World Health Organization,covering countries of the China,United States,United Kingdom,Australia,Serbia and Italy. The susceptible-exposed-infected-recovered (SEIR) model was generalized and then its parameters were optimized. According to the parameters in the basic infection number expression,the sensitivity in the system dynamics model was used to quantitatively analyze the influence of the protection rate,infection rate and average quarantine time on the early spread of the outbreak. Based on the analysis results,targeted prevention and control measures for the early outbreak of COVID-19 were proposed. Results:The generalized SEIR model had a good fit for the early prediction and evaluation of COVID-19 outbreaks in six countries. The spread of COVID-19 was mainly affected by the protection rate,infection rate and average quarantine time. The improvement of the protection rate in the first 10?days was the most important:the greater the protection rate,the fewer the number of confirmed cases. The infection rate in the first 5 days was the most critical:the smaller the infection rate,the fewer the number of confirmed cases. The average quarantine time in the first 5 days was very important:the shorter the average quarantine time,the fewer the number of confirmed cases. Through the comparison of key parameters of six countries,Australia and China had implemented strict epidemic prevention policies,which had resulted in good epidemic prevention effects. Conclusion:In the early stage of the outbreak,it is necessary to improve the protection rate,shorten the average quarantine time,and implement strict isolation policies to curb the spread of COVID-19.



Key wordsCoronavirus disease 2019      Susceptible-exposed-infectious-recovered model      System dynamics model      Sensitivity analysis      Epidemic prevention and control     
Received: 17 August 2020      Published: 16 May 2021
CLC:  R181.2  
  R181.2  
  A  
Corresponding Authors: CUI Zhiwei     E-mail: dongshi@chd.edu.cn;2019223026@chd.edu.cn
Cite this article:

DONG Shi,CUI Zhiwei,PAN Xiaoxiong,WANG Jianwei,GAO Chao. Exploring early prevention and control of COVID-19 outbreak based on system dynamics model analysis. J Zhejiang Univ (Med Sci), 2021, 50(1): 41-51.

URL:

http://www.zjujournals.com/med/10.3724/zdxbyxb-2021-0035     OR     http://www.zjujournals.com/med/Y2021/V50/I1/41


基于系统动力学模型的 2019冠状病毒病早期防控机制研究

目的:探讨各国2019冠状病毒病(COVID-19)暴发早期防控的效果,为传染病疫情暴发早期的防控提供对策。 方法:以世界卫生组织公开的中国、美国、英国、澳大利亚、塞尔维亚和意大利COVID-19疫情暴发早期数据为样本,建立广义易感-暴露-感染-恢复(SEIR)模型,对其参数进行最优化求解。然后,根据基本传染数表达式中的参数,利用系统动力学模型中的敏感性分析,定量分析各国保护率、感染率和平均检疫时间对疫情暴发早期的影响。最后,根据分析结果提出COVID-19暴发早期的防控对策。 结果:广义SEIR模型对六国COVID-19暴发早期的预测和评估具有较好的拟合性,实际数据与拟合数据高度重合。COVID-19扩散主要受保护率、感染率和平均检疫时间影响:从保护率来看,前 10?d的保护率提高最为重要,保护率越大,确诊人数越少;从感染率来看,前 5?d的感染率最为关键,感染率越小,确诊人数越少;从平均检疫时间来看,前 5?d的平均检疫时间至关重要,平均检疫时间越短,确诊人数越少。通过对六国关键参数对比发现,澳大利亚和中国由于实行严格的防疫政策,保护率较高,平均检疫时间较短,因而防疫效果较好。 结论:在COVID-19暴发早期,需要实行提高保护率、缩短平均检疫时间的措施,以及严格的隔离政策,抑制COVID-19传播及扩散。


关键词: 2019冠状病毒病,  易感-暴露-感染-恢复模型,  系统动力学模型,  敏感性分析,  疫情防控 
Figure 1 Cumulative number of confirmed cases in the early stage of coronavirus disease 2019 outbreak in six countries
{ d S ( t ) d t = ? α S ( t ) ? β S ( t ) I ( t ) N d E ( t ) d t = ? γ E ( t ) + β S ( t ) I ( t ) N d I ( t ) d t = γ E ( t ) ? δ I ( t ) d Q ( t ) d t = δ I ( t ) ? λ ( t ) Q ( t ) ? κ ( t ) Q ( t ) d R ( t ) d t = λ ( t ) Q ( t ) d D ( t ) d t = κ ( t ) Q ( t ) d P ( t ) d t = α S ( t ) (1)
 
κ ( t ) = κ 0 e ? κ 1 t (2)
 
λ ( t ) = λ 0 1 + e [ ? λ 1 ( t ? τ ) ] (3)
 
Figure 2 Flowchart of the generalized susceptible-exposed-infectious-recovered model

国家

保护率( α

感染率( β

平均潜伏时间( γ –1

平均检疫时间( δ –1

治愈率( λ

病死率( κ

总人口数( N

美国

0.0331

0.5995

1.0096

3.126 0

0.013000/0.019 3/0.0088

0.007400/0.0210

329466283

中国

0.0335

1.0000

1.0000

1.622 1

0.692700/0.0888/59.6739

0.005 200/0.0296

1404676330

意大利

0.0934

0.9660

7.0028

3.4614

0.016700/0.9424/40.4657

0.021700/0.0380

60461828

英国

0.0356

0.5906

1.7126

4.3290

0.000688/0.9420/40.2121

0.024300/0.0158

67886004

澳大利亚

0.2883

1.0000

2.6042

5.1256

0.033300/0.2120/11.8151

0.000 605/0.000056

25459700

塞尔维亚

0.026 3

0.5208

2.2665

4.5455

0.066000/5.0000/26.8389

0.007 900/0.0704

8737370

Table 1 Optimal parameters of generalized susceptible-exposed-infectious-recovered model in six countries
Figure 3 Comparison of fitted data and actual data on current infections,cured and dead persons in six countries
Figure 4 Sensitivity analysis of protection rate to the number of coronavirus disease 2019 patients in six countries
Figure 5 Sensitivity analysis of infection rate to the number of coronavirus disease 2019 patients in six countries
Figure 6 Sensitivity analysis of average quarantine rate to the number of coronavirus disease 2019 patients in six countries
Figure 7 Comparison of early protection rate and average quarantine time of coronavirus disease 2019 outbreak in six countries
Figure 8 Proportion of early infection in coronavirus disease 2019 outbreak in six countries
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