| 多阶段动态时滞动力学模型的COVID-19传播分析 |
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| 引用本文： | 张李盈,李东宸,任景莉.多阶段动态时滞动力学模型的COVID-19传播分析[J].武汉大学学报(信息科学版),2020(5):658-666. |
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| 作者姓名： | 张李盈 李东宸 任景莉 |
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| 作者单位： | 郑州大学数学与统计学院;郑州大学河南省大数据研究院 |
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| 基金项目： | 中国工程院重大咨询研究项目(2020-ZD-16);国家自然科学基金(11771407)。 |
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| 摘 要： | 截至2020-04-21,全球累计确诊新型冠状病毒肺炎(coronavirus disease 2019,COVID-19)病例数已超过245万人,死亡病例数超过17万人。根据疫情的发展过程,首先建立了改进的离散时间多阶段时滞动力学模型,以提取疫情的传播特征,解析防控干预的影响(防控干预效果)和医疗资源可用率的影响,并基于该模型,提出一种分析COVID-19的经验传递动力学方法。其中,经验提取是基于该模型与WHO(World Health Organization)发布的疫情数据,通过参数反演实现。然后利用该方法,分析了意大利、西班牙、德国和美国等国家疫情所处的阶段,预测不同措施下各国疫情的可能走向,给出了快速控制的建议。分析结果显示,中国疫情已基本得到控制,西班牙、德国、意大利已达到峰值,美国疫情正处于紧急防御期。依据经验传递动力学方法,建议西班牙、德国、意大利三国继续坚持目前的防控干预方式,美国加大防控力度,尽快使疫情进入可控阶段。
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| 关 键 词： | 新型冠状病毒肺炎 离散时滞动力系统 多阶段时滞动力学模型 疫情预测 |
Analysis of COVID-19 by Discrete Multi-stage Dynamics System with Time Delay |
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| ZHANG Liying,LI Dongchen,REN Jingli.Analysis of COVID-19 by Discrete Multi-stage Dynamics System with Time Delay[J].Geomatics and Information Science of Wuhan University,2020(5):658-666. |
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| Authors: | ZHANG Liying LI Dongchen REN Jingli |
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| Institution: | (School of Mathematics and Statistics,Zhengzhou University,Zhengzhou 450001,China;Big Data Research Institute of Henan Province,Zhengzhou University,Zhengzhou 450001,China) |
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| Abstract: | Coronavirus disease 2019(COVID-19) has broken out worldwide. Up to Apr.21,2020, more than 2.45 million confirmed cases have been diagnosed, and more than 0.17 million deaths have been reported.Based on the development process of China’ s epidemic, this paper proposes an improved discrete-time multi-stage time-delay dynamic model to extract the transmission characteristics of epidemic, the impact of prevention and control interventions(prevention and control intervention effect) and the impact of medical resource availability, and establishes an empirical transmission dynamics method of COVID-19 analysis.Among them, the experience extraction is based on the model and the epidemic data released by World Health Organization(WHO), and realized by parameter inversion. Furthermore, by using the proposed method, this paper analyzes the epidemic stages in Italy, Spain, Germany and the United States, predicts the possible trend of epidemic situation in different countries under different measures, and gives suggestions on rapid control. Analysis results show that the China’ s epidemic has been basically controlled,Spain, Germany and Italy have reached the peak, and the United States is in a rapid growth period.According to the empirical transfer dynamics method, Spain, Germany and Italy should continue to adhere to the current prevention and control intervention mode, and the United States should intensify the efforts of prevention and control and make the epidemic enter the controllable stage as soon as possible. |
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| Keywords: | coronavirus disease 2019(COVID-19) discrete dynamic system with time delay multi-stage dynamic model with time delay prediction of epidemic |
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