基于COVID-19传播特性的传染病模型的构建与研究

doi:10.13306/j.1672-3813.2023.02.004

复杂系统与复杂性科学

2023, Vol. 20

Issue (2): 29-37 DOI: 10.13306/j.1672-3813.2023.02.004

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基于COVID-19传播特性的传染病模型的构建与研究

朱懋昌, 宾晟, 孙更新

青岛大学计算机科学技术学院,山东青岛 266071

Construction and Research of Infectious Disease Model Based on COVID-19 Transmission Characteristics

ZHU Maochang, BIN Sheng, SUN Gengxin

School of Computer Science and Technology, Qingdao University, Qingdao 266071, China

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摘要为了更好地揭示新冠肺炎(COVID-19)的传播机理,通过分析新冠病毒(2019-nCoV)的传播特性,考虑隐性潜伏者的自愈以及潜伏者的提前隔离,引入“入院隔离状态”,“隐性治愈状态”,考虑防控强度的变化,引入“发病状态”,提出了SEAIHR动力学模型。利用真实疫情数据,考虑不同阶段参数的变化,进行了多模型对比试验。实验结果表明,SEAIHR模型拟合和预测精度有明显提升,较经典模型在疫情前中期降低了34.4%~72.8%拟合误差,为疫情防控提供了参考与指导。

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	朱懋昌
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	孙更新

关键词 ： SEIR, 隐性潜伏者, COVID-19, 动力学模型

Abstract：In order to better reveal the transmission mechanism of COVID-19, this paper proposes the SEAIHR dynamic model by analyzing the transmission characteristics of COVID-19, considering the self-healing of the hidden lurks and the early isolation of the lurks, introducing “h hospitalization isolation”, “recessive cure”, considering the change of prevention and control intensity, and introducing “morbidity status”. Using the real epidemic data and considering the changes of parameters in different stages, a multi model comparative test was conducted. The experimental results showed that the fitting and prediction accuracy of the SEAIHR model was significantly improved, and the fitting error was 34.4%~72.8% lower than that of the classical model in the early and middle stages of the epidemic, providing reference and guidance for epidemic prevention and control.

Key words： SEIR hidden lurker COVID-19 dynamic model

收稿日期: 2022-04-27 出版日期: 2023-07-21

ZTFLH:	O29
	TP391

基金资助:山东省自然基金面上项目(ZR2021MG006);山东省社会科学规划项目(17CHLJ16)

通讯作者: 孙更新(1978-),男,山东青岛人,博士,副教授,主要研究方向为复杂网络,复杂网络中传播动力学及相关传播模型。

作者简介: 朱懋昌(1997-),男,山东济宁人,硕士研究生,主要研究方向为复杂网络。

引用本文:

朱懋昌, 宾晟, 孙更新. 基于COVID-19传播特性的传染病模型的构建与研究[J]. 复杂系统与复杂性科学, 2023, 20(2): 29-37.
ZHU Maochang, BIN Sheng, SUN Gengxin. Construction and Research of Infectious Disease Model Based on COVID-19 Transmission Characteristics. Complex Systems and Complexity Science, 2023, 20(2): 29-37.

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https://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2023.02.004 或 https://fzkx.qdu.edu.cn/CN/Y2023/V20/I2/29

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