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
Link To Document :
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