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    Visual Analysis of Probabilistic Infection Contagion in Hospitals

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    Date
    2019
    Author
    Wunderlich, Marcel ORCID
    Block, Isabelle
    von Landesberger, Tatiana ORCID
    Petzold, Markus ORCID
    Marschollek, Michael
    Scheithauer, Simone
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    Abstract
    Clinicians 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.
    BibTeX
    @inproceedings {10.2312:vmv.20191328,
    booktitle = {Vision, Modeling and Visualization},
    editor = {Schulz, Hans-Jörg and Teschner, Matthias and Wimmer, Michael},
    title = {{Visual Analysis of Probabilistic Infection Contagion in Hospitals}},
    author = {Wunderlich, Marcel and Block, Isabelle and von Landesberger, Tatiana and Petzold, Markus and Marschollek, Michael and Scheithauer, Simone},
    year = {2019},
    publisher = {The Eurographics Association},
    ISBN = {978-3-03868-098-7},
    DOI = {10.2312/vmv.20191328}
    }
    URI
    https://doi.org/10.2312/vmv.20191328
    https://diglib.eg.org:443/handle/10.2312/vmv20191328
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