Multimodal Epidemic Visual Analytics and Modeling

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dc.contributor.authorJang, Yun
dc.contributor.authorKim, Seokyeon
dc.date.accessioned2020-12-24T19:16:34Z
dc.date.available2020-12-24T19:16:34Z
dc.date.issued2021-01-05
dc.description.abstractThe risk of infectious disease increases due to various factors including the dense population, development of various transportations, urbanization, and abnormal weather conditions. Since the speed of epidemic spread is fast, it is necessary to respond quickly in order to prevent the high fatality rate. Therefore, a fast search for the highly accurate spreading model has to be focused on the proper analysis of disease spreading. There have been many studies to understand the disease spreading and the epidemic model is often used to analyze and predict the spread of infectious disease. However, it is limited to apply the epidemic model for the spread analysis because the model captures spreading changes only within the defined area. In this paper, we propose a framework for the disease spreading simulation with multimodal factors in the epidemic model and networks of possible spread routes. Our system provides an interactive simulation environment with the interregional disease spreading according to various spread parameters. Moreover, in order to understand the spreading directions, we extract vector fields over time and visualize the vector fields with the fatality of the disease. Therefore, users are able to understand the disease spreading phenomena and obtain appropriate models through our framework.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2021.175
dc.identifier.isbn978-0-9981331-4-0
dc.identifier.urihttp://hdl.handle.net/10125/70787
dc.language.isoEnglish
dc.relation.ispartofProceedings of the 54th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectInteractive Visual Analytics and Visualization for Decision Making
dc.subjectepidemic models
dc.subjectvisual analytics
dc.titleMultimodal Epidemic Visual Analytics and Modeling
prism.startingpage1447

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