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Epidemic Modelling by Ripple-Spreading Network and Genetic Algorithm
Joint Authors
Hu, Xiao-Bing
Leeson, Mark S.
Liao, Jian-Qin
Wang, Ming
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-11-03
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Liao, Jian-Qin& Hu, Xiao-Bing& Wang, Ming& Leeson, Mark S.. 2013. Epidemic Modelling by Ripple-Spreading Network and Genetic Algorithm. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-11.
https://search.emarefa.net/detail/BIM-1031938
Modern Language Association (MLA)
Liao, Jian-Qin…[et al.]. Epidemic Modelling by Ripple-Spreading Network and Genetic Algorithm. Mathematical Problems in Engineering No. 2013 (2013), pp.1-11.
https://search.emarefa.net/detail/BIM-1031938
American Medical Association (AMA)
Liao, Jian-Qin& Hu, Xiao-Bing& Wang, Ming& Leeson, Mark S.. Epidemic Modelling by Ripple-Spreading Network and Genetic Algorithm. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-11.
https://search.emarefa.net/detail/BIM-1031938
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1031938