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dc.contributor.authorWunderlich, Marcelen_US
dc.contributor.authorBlock, Isabelleen_US
dc.contributor.authorvon Landesberger, Tatianaen_US
dc.contributor.authorPetzold, Markusen_US
dc.contributor.authorMarschollek, Michaelen_US
dc.contributor.authorScheithauer, Simoneen_US
dc.contributor.editorSchulz, Hans-Jörg and Teschner, Matthias and Wimmer, Michaelen_US
dc.description.abstractClinicians and hygienists need to know how an infection of one patient could be transmitted among other patients in the hospital (e.g., to prevent outbreaks). They need to analyze how many and which patients will possibly be infected, how fast the infection could spread, and which contacts are likely to transfer the infections within the hospital. Currently, infection contagion is modeled and visualized for populations only on an aggregate level, without identification and exploration of possible infection between individuals. We present a novel visual analytics approach that simulates the contagion in a contact graph of patients in a hospital. We propose a clustering approach to identify probable contagion scenarios in the simulation ensemble. Furthermore, our novel visual design for detailed assessment of transmission shows the temporal development of contagion per patient in one view. We demonstrate the capability of our approach to a real-world use case in a German hospital.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman centered computing
dc.subjectGraph drawings
dc.subjectVisual analytics
dc.titleVisual Analysis of Probabilistic Infection Contagion in Hospitalsen_US
dc.description.seriesinformationVision, Modeling and Visualization
dc.description.sectionheadersVisualization and Visual Analytics

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  • VMV19
    ISBN 978-3-03868-098-7

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