Journal of Shandong University (Health Sciences) ›› 2020, Vol. 58 ›› Issue (10): 20-24.doi: 10.6040/j.issn.1671-7554.0.2020.0775

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Construction of SEIQCR epidemic model and its application in the evaluation of public health interventions on COVID-19 in Guangzhou

XU Lijun1*, LIU Wenhui2*, LIU Yuan2, LI Meixia2, LUO Lei2, OU Chunquan1   

  1. 1. Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou 510515, Guangdong, China;
    2. Guangzhou Center for Disease Control and Prevention, Guangzhou 510515, Guangdong, China
  • Online:2020-10-10 Published:2020-10-08

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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

CLC Number: 

  • R181.2
[1] Chen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study[J]. The Lancet, 2020, 395(10223): 507-513.
[2] World Health Organization. Novel coronavirus(2019-nCoV)[EB/OL].(2020-01-30)[2020-03-04]. https://www.who.int/emergencies/diseases/novel-coronavirus-2019.
[3] Ai S, Zhu G, Tian F, et al. Population movement, city closure in Wuhan and geographical expansion of the 2019-nCoV pneumonia infection in China in January 2020[J]. Clin Infect Dis, 2020. doi: 10.1093/cid/ciaa422.
[4] 赖志鸿,黄碧玲.广州市统计年鉴-2019[Z/OL]. 北京:中国统计出版社,2019.
[5] Yang Z, Zeng Z, Wang K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions[J]. J Thorac Dis, 2020, 12(3): 165-174.
[6] Wan H, Cui J, Yang G. Risk estimation and prediction by modeling the transmission of the novel coronavirus(COVID-19)in mainland China excluding Hubei province[J]. medRxiv, 2020: 2020-2023. doi: 10.1101/2020.03.01.20029629.
[7] Mamo DK. Model the transmission dynamics of COVID-19 propagation with public health intervention[J]. Results in Applied Mathematics, 2020, 7: 100123. doi: 10.1016/j.rinam.2020.100123.
[8] Zhou X, Ma X, Hong N, et al. Forecasting the Worldwide Spread of COVID-19 based on Logistic Model and SEIR Model[J]. medRxiv, 2020: 2020-2023. doi: 10.1101/2020.03.26.20044289.
[9] Tang Z, Li X, Li H. Prediction of new coronavirus infection based on a modified SEIR model[J]. medRxiv, 2020: 2020-2023. doi: 10.1101/2020.03.03.20030858.
[10] Mahmud A, Lim PY. Applying the SEIR model in forecasting the COVID-19 trend in malaysia: a preliminary study[J]. medRxiv, 2020: 2020-2024. doi: 10.1101/2020.04.14.20065607.
[11] 崔玉美,陈姗姗,傅新楚. 几类传染病模型中基本再生数的计算[J]. 复杂系统与复杂性科学,2017, 14(4): 14-31.
[12] Wang J, Liao Y, Wang X, et al. Incidence of novel coronavirus(2019-nCoV)infection among people under home quarantine in Shenzhen, China[J]. Travel Med Infect Di, 2020: 101660. doi: 10.1016/j.tmaid.2020.101660.
[13] Liu Y, Tang JW, Lam TT. Transmission Dynamics of the COVID-19 Epidemics in England[J]. medRxiv, 2020: 2020-2026.doi: 10.1101/2020.06.30.20143743.
[14] Feehan D, Mahmud A. Quantifying population contact patterns in the United States during the COVID-19 pandemic[J]. medRxiv, 2020: 2020-2024. doi: 10.1101/2020.04.13.20064014.
[15] Utamura M, Koizumi M, Kirikami S. Isolation Considered Epidemiological Model for the Prediction of COVID-19 Trend in Tokyo, Japan[J]. medRxiv, 2020: 2020-2027. doi: 10.1101/2020.07.31.20165829.
[16] Ma Y, Zhao Y, Liu J, et al. Effects of temperature variation and humidity on the death of COVID-19 in Wuhan, China[J]. Sci Total Environ, 2020, 724:138226. doi: 10.1016/j.scitotenv.2020.138226.
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