• DocumentCode
    1757335
  • Title

    Tracking Infectious Disease Spread for Global Pandemic Containment

  • Author

    Kwok-Leung Tsui ; Wong, Zoie Shui-Yee ; Goldsman, David ; Edesess, Michael

  • Author_Institution
    City Univ. of Hong Kong, Hong Kong, China
  • Volume
    28
  • Issue
    6
  • fYear
    2013
  • fDate
    Nov.-Dec. 2013
  • Firstpage
    60
  • Lastpage
    64
  • Abstract
    Simulation studies play a significant role in supporting pandemic disease scenario prediction and facilitating the understanding of how infectious diseases spread. This is of paramount importance for the anticipation, mitigation, and containment of pandemics. Disease-spread simulation models are often used to understand the effects of changes in citizen behavior or government policies, or to study disease outbreak parameters and mitigation-strategy features. Here, we focus on how to improve future global pandemic containment with the help of advanced artificial intelligence and simulation methods.
  • Keywords
    artificial intelligence; diseases; health care; medical diagnostic computing; artificial intelligence; disease outbreak parameter; disease-spread simulation model; global pandemic containment; infectious disease; pandemic anticipation; pandemic disease scenario prediction; pandemic mitigation; Computational modeling; Diseases; Integrated circuit modeling; Sociology; Solid modeling; Statistics; AI; artificial intelligence; infectious diseases; intelligent systems; simulation; virus containment;
  • fLanguage
    English
  • Journal_Title
    Intelligent Systems, IEEE
  • Publisher
    ieee
  • ISSN
    1541-1672
  • Type

    jour

  • DOI
    10.1109/MIS.2013.149
  • Filename
    6733224