Infectious Disease Patterns Analysis Based on Visualization of Multidimensional Space-Time Data

被引：0
|
作者：
Jin S. [1 ]
Tao Y. [1 ]
Yan Y. [1 ]
Dai H. [1 ]
机构：
[1] State Key Laboratory of CAD & CG, Zhejiang University, Hangzhou
来源：
Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics | 2019年 / 31卷 / 02期
关键词：
Multivariable space-temporal data; Patterns of infectious disease; Visual analysis;
D O I：
10.3724/SP.J.1089.2019.17653
中图分类号：
学科分类号：
摘要：
In recent years, the outbreak of infectious diseases, such as SARS (severe acute respiratory syndromes), influenza A (H1N1), and hand-foot-and-mouth disease, has caused a widespread concern in our society. The outbreak of infectious diseases is often seasonal, spatial, and related. To intuitively analyze the spatial-temporal patterns of infectious diseases, interactively mining regional associations and similarities between different diseases, this paper presents a visual analysis system for infectious diseases. The seasonal and annual patterns of infectious diseases are visualized by stack graphs and line charts, and abnormal events can be extracted from a temporal parallel coordinate and regional distribution comparison bars. The spatial distribution patterns of diseases are encoded in the choropleth map to analyze the spatial clustering results and their similarities. According to the analysis of the overall, individual trends and outliers of 39 statutory infectious diseases, it is shown that the system can comprehensively explore the multi-dimensional temporal and spatial characteristics of infectious diseases and effectively help users to discover the implicit temporal and spatial patterns, and thus better prevent, control and analyze the infectious diseases. © 2019, Beijing China Science Journal Publishing Co. Ltd. All right reserved.
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页码：241 / 255
页数：14
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