• DocumentCode
    1452382
  • Title

    Epinome: A Visual-Analytics Workbench for Epidemiology Data

  • Author

    Livnat, Y. ; Rhyne, T. ; Samore, M.

  • Author_Institution
    Univ. of Utah, Salt Lake City, UT, USA
  • Volume
    32
  • Issue
    2
  • fYear
    2012
  • Firstpage
    89
  • Lastpage
    95
  • Abstract
    Early detection and rapid response to infectious-disease outbreaks rely on effective decision making based on information from disparate sources. To improve decision-making in outbreak detection and response, it´s important to understand how public health practitioners seek relevant information. Epinome, a user-centric visual-analytics system, supports research on decision-making in public health, particularly evaluation of information search strategies. Epinome facilitates investigation of scripted high-fidelity large-scale simulated disease outbreaks. Its dynamic environment seamlessly evolves and adapts as the user´s tasks and focus change. This video shows how the Epinome system facilitates interactive simulations of disease outbreaks.
  • Keywords
    data analysis; data visualisation; decision making; digital simulation; diseases; epidemics; health care; interactive systems; Epinome; early detection; effective decision making; epidemiology data; infectious disease outbreaks; interactive simulations; public health practitioners; rapid response; scripted high fidelity large scale simulated disease outbreaks; user centric visual analytics system; visual analytics workbench; Adaptation models; Decision making; Diseases; Medical expert systems; Medical information systems; Public healthcare; Search problems; Visualization; applications; coordinated multiple-views; epinome; infectious disease outbreak; information visualization; simulations; user study; visual analytics;
  • fLanguage
    English
  • Journal_Title
    Computer Graphics and Applications, IEEE
  • Publisher
    ieee
  • ISSN
    0272-1716
  • Type

    jour

  • DOI
    10.1109/MCG.2012.31
  • Filename
    6155166