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A time delay dynamical model for outbreak of 2019-nCoV and the parameter identification

机译:2019-NCOV爆发的时间延迟动态模型及参数识别

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摘要

In this paper, we propose a novel dynamical system with time delay to describe the outbreak of 2019-nCoV in China. One typical feature of this epidemic is that it can spread in the latent period, which can therefore be described by time delay process in the differential equations. The accumulated numbers of classified populations are employed as variables, which is consistent with the official data and facilitates the parameter identification. The numerical methods for the prediction of the outbreak of 2019-nCoV and parameter identification are provided, and the numerical results show that the novel dynamic system can well predict the outbreak trend so far. Based on the numerical simulations, we suggest that the transmission of individuals should be greatly controlled with high isolation rate by the government.
机译:在本文中,我们提出了一种新的动态系统,随着时间延迟描述2019-NCOV在中国的爆发。 这种疫情的一个典型特征是它可以在潜在的时段中传播,因此可以在微分方程中通过时间延迟过程描述。 累积数量的分类群体被用作变量,这与官方数据一致,并促进参数识别。 提供了预测2019-NCOV和参数识别爆发的数值方法,数值结果表明,新颖的动态系统可以很好地预测到目前为止的爆发趋势。 基于数值模拟,我们建议,政府的高隔离率应大大控制个人的传播。

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