摘要
对新冠肺炎疫情数据进行可视分析,可以直观展示疫情动态、挖掘疫情传播规律、预测疫情发展趋势.以开源渠道获取的多维时空新冠肺炎疫情数据为基础,针对疫情数据的多维时空特征构建病例数量数据集、病例来源数据集和病例关系数据集.在数据预处理的基础上,综合应用时间轴交互、流行病数学模型等分析方法,提出一个新冠肺炎疫情可视化模型,采用递进式分析的方法对典型传染病疫情数据进行可视分析.以河南省的疫情数据为例,展示了新冠肺炎疫情态势,挖掘了新冠肺炎疫情来源特征,总结了新冠肺炎疫情传播模式,预测了新冠肺炎疫情未来趋势,为河南省新冠疫情防控提供了科学依据.
Visualization analysis of the COVID-19 epidemic data can directly display epidemic dynamics,explore the epidemic spreading rule,and predict the trend of epidemic development.Based on the COVID-19 epidemic data obtained by public channels such as Ding Xiang Yuan and ministries and health committees,According to the multi-dimensional spatial and temporal characteristics of epidemic data,three data sets are designed,namely,case number data set,case source data set and case relationship data set.A COVID-19 epidemic visualization model was proposed based on data preprocessing and comprehensive analysis of time axis interaction and SEIR model.Progressive epidemic analysis was used to visualize the epidemic situation of typical infectious diseases.Take Henan Province as an example,the epidemic situation of COVID-19 is revealed,the source characteristics of COVID-19 are excavated,the epidemic pattern of COVID-19 is summarized,and the future trend of COVID-19 is predicted.
作者
刘建湘
刘海砚
陈晓慧
李佳
康磊
赵清波
Liu Jianxiang;Liu Haiyan;Chen Xiaohui;Li Jia;Kang Lei;Zhao Qingbo(School of Data and Target Engineering,PLA Strategic Support Force,Information Engineering University,Zhengzhou 450001)
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2020年第10期1617-1627,共11页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(41801313,41901397).
关键词
新冠肺炎
可视化模型
多维时空
流行病数学模型
COVID-19
visualization model
multidimensional space-time
mathematical models of epidemic diseases
