摘要
基于病毒动力学传染机制,构建了考虑不同时期防控措施影响下的新型冠状病毒肺炎(COVID-19)阶段式传播模型.依据空间上的严重性将全国划分为三类疫情区,对各疫情区传染人数进行了阶段式模拟.结合上述模拟结果,进一步量化评估了各疫情区所采取的如武汉交通管制、对口支援湖北和小区封闭式管理等措施对抑制病毒传播的影响.结果表明,阶段式传播模型能够较好地模拟出各疫情区不同时期传染人数的变化特征,政府采取的交通管制和小区封闭式管理等防控措施大幅减少了传染人数,感染人数呈现出大幅下降的趋势,有效抑制了COVID-19的大规模扩散.
A staged transmission model for Corona Virus Disease 2019(COVID⁃19)was built based on virus in⁃fection dynamics considering prevention and control measures during different periods.The whole country is classified into three level of epidemic areas according to the seriousness of COVID⁃19,and the number of infected people in each epidemic area is simulated in a staged way.Based on analysis of the simulation results,the impact of measures taken in each epidemic area,such as the traffic control in Wuhan,the counterpart support to Hubei,and the closed community management,on the suppression of virus transmission was further evaluated.The results show that the staged transmission model can well model the changing characteristics of the number of infected people dur⁃ing different periods in each epidemic area.The prevention and control measures practiced by government,such as the traffic control in Wuhan and the closed community management,have significantly inhibited the spreading of COVID⁃19,indicated by the substantial downward trend in the number of infected people.
作者
朱连华
谭岩
肖惠文
王露薇
李安琪
何陈涛
ZHU Lianhua;TAN Yan;XIAO Huiwen;WANG Luwei;LI Anqi;HE Chentao(School of Mathematics and Statistics,Nanjing University of Information Science&Technology,Nanjing 210044;Changwang School of Honors,Nanjing University of Information Science&Technology,Nanjing 210044;School of Environmental Science and Engineering,Nanjing University of Information Science&Technology,Nanjing 210044;School of Geographical Science,Nanjing University of Information Science&Technology,Nanjing 210044)
出处
《南京信息工程大学学报(自然科学版)》
CAS
2020年第3期364-372,共9页
Journal of Nanjing University of Information Science & Technology(Natural Science Edition)
基金
国家重点研发计划(2017YFA0603804)
国家自然科学基金(41875098)
江苏省自然科学基金(BK20191394)
江苏省统计研究重点课题(2019A005)
大学生创新训练计划项目(201810300067Y)。