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Liu Jianxiang, Liu Haiyan, Chen Xiaohui, Li Jia, Kang Lei, Zhao Qingbo. Visual Analysis Method for COVID-19 Epidemic Situation[J]. Journal of Computer-Aided Design & Computer Graphics, 2020, 32(10): 1617-1627. DOI: 10.3724/SP.J.1089.2020.18466
Citation: Liu Jianxiang, Liu Haiyan, Chen Xiaohui, Li Jia, Kang Lei, Zhao Qingbo. Visual Analysis Method for COVID-19 Epidemic Situation[J]. Journal of Computer-Aided Design & Computer Graphics, 2020, 32(10): 1617-1627. DOI: 10.3724/SP.J.1089.2020.18466

Visual Analysis Method for COVID-19 Epidemic Situation

  • 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.
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