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引入异质控制因素的传染病传播网络动态模型。

Network dynamic model of epidemic transmission introducing a heterogeneous control factor.

机构信息

Graduate School of National Defense University, Beijing, China.

Joint Operation College of National Defense University, Beijing, China.

出版信息

J Med Virol. 2021 Dec;93(12):6496-6505. doi: 10.1002/jmv.27025. Epub 2021 May 28.

Abstract

The COVID-19 epidemic is not only a medical issue but also a sophisticated social problem. We propose a network dynamics model of epidemic transmission introducing a heterogeneous control factor. The proposed model applied the classical susceptible- exposed-infectious-recovered model to the network based on effective distance and was modified by introducing a heterogeneous control factor with temporal and spatial characteristics. International aviation data were approximately used to estimate the flux fraction matrix, and the effective distance was calculated. Through parameter estimation and simulation, the theoretical values of the modified model fit well with practical values. By adjusting the parameters and observing the change of the results, we found that the modified model is more in line with the actual needs and has higher credibility in the comprehensive analysis. The assessment shows that the number of confirmed cases worldwide will reach about 20 million optimistically. In severe cases, the peak value will exceed 80 million, and the late stage of the epidemic shows a long tail shape, lasting more than one and a half years. The effective way to control the global epidemic is to strengthen international cooperation and to impose international travel restrictions and other measures.

摘要

新冠疫情不仅是一个医学问题,也是一个复杂的社会问题。我们提出了一个引入异质控制因素的传染病传播网络动力学模型。该模型将经典的易感-暴露-感染-恢复模型应用于基于有效距离的网络,并通过引入具有时空特征的异质控制因素进行了修正。我们使用了国际航空数据来近似估计通量分数矩阵,并计算了有效距离。通过参数估计和模拟,修正模型的理论值与实际值拟合良好。通过调整参数并观察结果的变化,我们发现修正模型更符合实际需求,在综合分析中具有更高的可信度。评估显示,全球确诊病例数乐观估计将达到约 2000 万例。在严重情况下,峰值将超过 8000 万例,疫情后期呈现长尾形状,持续时间超过一年半。控制全球疫情的有效方法是加强国际合作,并实施国际旅行限制和其他措施。

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