DocumentCode :
3220875
Title :
An approach to model the interventions of unconventional emergency
Author :
Zhang Laobing ; Chen Bin ; Liu Liang ; Ge Yuanzheng ; Qiu Xiaogang
Author_Institution :
Coll. of Inf. Syst. & Manage., Nat. Univ. of Defense Technol., Changsha, China
fYear :
2013
fDate :
28-30 July 2013
Firstpage :
602
Lastpage :
606
Abstract :
Aim at preventing, or controlling if prevention is not possible, the spread of disease. We model several types of commonly-used government interventions in order to quantify this research. Finally we computationally tested the models using an artificial campus. The results show: 1) Campus pandemics extinguish even without intervention 2) Small scale inoculation programs are ineffectual, but large scale inoculation programs will bring non-linear increases in benefits 3) Identifying and isolating the infectious and their `strong social group´ quickly dramatically lowers spread 4)Isolation Plus Close Public-space Intervention will decrease the peak value and the last time. This study can support quantitative experimentation and prediction of infectious diseases within predefined areas, and assessment of intervention strategies.
Keywords :
artificial intelligence; diseases; emergency management; government; artificial campus; campus pandemics; close public-space intervention; government intervention; large scale inoculation program; small scale inoculation program; unconventional emergency; Chapters; Computational modeling; Diseases; Government; Influenza; Loading; Sociology; agent-based modeling; artificial society; computational experiments; influenza transmission; intervention;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Service Operations and Logistics, and Informatics (SOLI), 2013 IEEE International Conference on
Conference_Location :
Dongguan
Print_ISBN :
978-1-4799-0529-4
Type :
conf
DOI :
10.1109/SOLI.2013.6611485
Filename :
6611485
Link To Document :
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