摘要
2019年12月,新型冠状病毒肺炎(novel coronavirus pneumonia,NCP)疫情从武汉开始暴发,几天内迅速传播到全国乃至海外.科学有效地掌控疫情发展对疫情防控至关重要.本文基于全国各级卫生健康委员会每日公布的累计确诊数和治愈数,提出一类基于时滞动力学系统的传染病动力学模型.在模型中引入时滞过程,用来描述病毒潜伏期和治疗周期.通过公布的疫情数据,首先准确反演模型的参数;其次有效地模拟目前疫情的发展,并预测疫情未来的趋势;最后分析各级政府防控措施手段的有效程度,并发现在现有的高效防控措施下,疫情将在近期好转.
In late December 2019,a series of novel coronavirus pneumonia(NCP)cases emerged in Wuhan,and the outbreak of NCP began to spread rapidly to the whole country and even overseas within a few days.The scientific and effective understanding of epidemic development is essential for the prevention and control.In this paper,based on the cumulative number of confirmed and cured cases reported daily by the National Health Committee,we propose a novel dynamic system with time-delay to describe the outbreak of NCP.The time-delay process is introduced to describe the latent period and treatment cycle.Numerical simulations show that the parameters in the model are identified accurately,and the trend of the outbreak of NCP is effectively simulated.Moreover,the prediction for the tendency of NCP is provided for reference.Finally,we would conclude that the situation would be better and better under the current effective and efficient measures of government.
作者
严阅
陈瑜
刘可伋
罗心悦
许伯熹
江渝
程晋
Yue Yan;Yu Chen;Keji Liu;Xinyue Luo;Boxi Xu;Yu Jiang;Jin Cheng
出处
《中国科学：数学》
CSCD
北大核心
2020年第3期385-392,共8页
Scientia Sinica：Mathematica
基金
国家自然科学基金(批准号:11971121)
上海科学技术委员会“上海青年科技启明星计划”(批准号:19QA1403400)资助项目.
关键词
新型冠状病毒肺炎
时滞动力学模型
参数反演
疫情预测
novel coronavirus pneumonia
dynamic system with time delay
parameter identification
epidemic prediction
作者简介
严阅,E-mail:yan.yue@mail.shufe.edu.cn;陈瑜,E-mail:yuchen@sufe.edu.cn;刘可伋,E-mail:liu.keji@sufe.edu.cn;罗心悦,E-mail:vera@163.sufe.edu.cn;许伯熹,E-mail:xu.boxi@mail.shufe.edu.cn;江渝,E-mail:jiang.yu@mail.shufe.edu.cn;通信作者:程晋,E-mail:jcheng@fudan.edu.cn
