DocumentCode :
1735176
Title :
Gaming to Predict Human Responses to Mass Casualty Events: An Approach for Quick Look Tools for Pandemic Influenza
Author :
Brigantic, Robert T. ; Muller, George A. ; Taylor, Aimee E. ; Papatyi, Anthony F.
Author_Institution :
Nat. Security Directorate, Pacific Northwest Nat. Lab., Richland, WA, USA
Volume :
4
fYear :
2009
Firstpage :
1194
Lastpage :
1198
Abstract :
There is a need to better understand and describe social intelligence in the realm of dealing with mass casualty events, such as pandemic influenza, earthquakes, or other natural or manmade disasters. This social intelligence is needed to be able to accurately feed and drive models and simulations that attempt to describe and quantify human responses to such mass casualty events and potential mitigation strategies that might be used to minimize their impacts by reducing numbers of deaths, injuries, and other societal (e.g., economic) consequences. We propose to attempt to gain a better understanding of social intelligence and socially driven human responses through the use of games and game like interfaces with an application toward infectious diseases.
Keywords :
artificial intelligence; behavioural sciences; game theory; death consequence; game like interface; human response prediction; infectious disease; injuries consequence; mass casualty event; pandemic influenza; potential mitigation strategy; social intelligence; Discrete event simulation; Diseases; Earthquakes; Feeds; Humans; Influenza; Injuries; Medical services; National security; Public healthcare; Mass casualty; agent based modeling; pandemic influenza; quick look tools; social behavior;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Science and Engineering, 2009. CSE '09. International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4244-5334-4
Electronic_ISBN :
978-0-7695-3823-5
Type :
conf
DOI :
10.1109/CSE.2009.388
Filename :
5283062
Link To Document :
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