Liao, Jian-Qin, Hu, Xiao-Bing, Wang, Ming and Leeson, Mark S. (2013) Epidemic modelling by ripple-spreading network and genetic algorithm. Mathematical Problems in Engineering, Volume 2013 . Article number 506240. doi:10.1155/2013/506240 ISSN 1024-123X .

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Abstract

Mathematical analysis and modelling is central to infectious disease epidemiology. This paper, inspired by the natural ripple-spreading phenomenon, proposes a novel ripple-spreading network model for the study of infectious disease transmission. The new epidemic model naturally has good potential for capturing many spatial and temporal features observed in the outbreak of plagues. In particular, using a stochastic ripple-spreading process simulates the effect of random contacts and movements of individuals on the probability of infection well, which is usually a challenging issue in epidemic modeling. Some ripple-spreading related parameters such as threshold and amplifying factor of nodes are ideal to describe the importance of individuals’ physical fitness and immunity. The new model is rich in parameters to incorporate many real factors such as public health service and policies, and it is highly flexible to modifications. A genetic algorithm is used to tune the parameters of the model by referring to historic data of an epidemic. The well-tuned model can then be used for analyzing and forecasting purposes. The effectiveness of the proposed method is illustrated by simulation results.

Item Type:	Journal Article
Subjects:	Q Science > QA Mathematics T Technology > T Technology (General)
Divisions:	Faculty of Science, Engineering and Medicine > Engineering > Engineering
Library of Congress Subject Headings (LCSH):	Algorithms, Computer science -- Mathematics, Epidemiology -- Research, Stochastic analysis, Communicable diseases -- Transmission
Journal or Publication Title:	Mathematical Problems in Engineering
Publisher:	Hindawi Publishing
ISSN:	1024-123X
Official Date:	2013
Dates:	Date Event 2013 Published
Volume:	Volume 2013
Number of Pages:	11
Page Range:	Article number 506240
DOI:	10.1155/2013/506240
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Date of first compliant deposit:	25 December 2015
Date of first compliant Open Access:	25 December 2015
Funder:	Seventh Framework Programme (European Commission) (FP7), Beijing shi fan da xue (China) [Beijing Normal University] (BNU), China. Guo jia ke xue ji shu bu [Ministry of Science and Technology] (CMST)
Grant number:	PIOF-GA-2011-299725 (FP7) ; 2012-RC-02 (BNU) ; 2012CB955404 (CMST)

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