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    • 39-Issue 1
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    A Survey of Visual Analytics for Public Health

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    Date
    2020
    Author
    Preim, Bernhard ORCID
    Lawonn, Kai ORCID
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    Abstract
    We describe visual analytics solutions aiming to support public health professionals, and thus, preventive measures. Prevention aims at advocating behaviour and policy changes likely to improve human health. Public health strives to limit the outbreak of acute diseases as well as the reduction of chronic diseases and injuries. For this purpose, data are collected to identify trends in human health, to derive hypotheses, e.g. related to risk factors, and to get insights in the data and the underlying phenomena. Most public health data have a temporal character. Moreover, the spatial character, e.g. spatial clustering of diseases, needs to be considered for decision‐making. Visual analytics techniques involve (subspace) clustering, interaction techniques to identify relevant subpopulations, e.g. being particularly vulnerable to diseases, imputation of missing values, visual queries as well as visualization and interaction techniques for spatio‐temporal data. We describe requirements, tasks and visual analytics techniques that are widely used in public health before going into detail with respect to applications. These include outbreak surveillance and epidemiology research, e.g. cancer epidemiology. We classify the solutions based on the visual analytics techniques employed. We also discuss gaps in the current state of the art and resulting research opportunities in a research agenda to advance visual analytics support in public health.
    BibTeX
    @article {10.1111:cgf.13891,
    journal = {Computer Graphics Forum},
    title = {{A Survey of Visual Analytics for Public Health}},
    author = {Preim, Bernhard and Lawonn, Kai},
    year = {2020},
    publisher = {© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.13891}
    }
    URI
    https://doi.org/10.1111/cgf.13891
    https://diglib.eg.org:443/handle/10.1111/cgf13891
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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA