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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hu, Xiao-Bing Wang, Ming Liao, Jian-Qin Leeson, Mark S. Hines, Evor L. Di Paolo, Ezequiel |
| Copyright Year | 2011 |
| Description | Author affiliation: Warwick Medical School, School of Engineering, University of Warwick, Coventry, UK (Liao, Jian-Qin; Leeson, Mark S.; Hines, Evor L.) || The State Key Laboratory of Earth, Surface Processes and Resource, Ecology, Beijing Normal University, Beijing, China (Hu, Xiao-Bing; Wang, Ming) || Ikerbasque, Basque Science, Foundation, Centre for Research on, Life, Mind and Society, University of the Basque Country, San Sebastian, Spain (Di Paolo, Ezequiel) |
| 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 of capturing many spatial and temporal features observed in the outbreak of plagues. In particular, using a stochastic ripple-spreading process can well simulate the effect of random contacts and movements of individuals on the probability of infection, 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 polices, and it is highly flexible to modifications. 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 propose method is illustrated by a preliminary study. |
| Starting Page | 1 |
| Ending Page | 7 |
| File Size | 595248 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781424478347 |
| e-ISBN | 9781424478354 |
| DOI | 10.1109/CEC.2011.5949995 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-06-05 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Mathematical model Diseases Analytical models Genetic algorithms Biological system modeling Computational modeling Data models Parameter Optimization Ripple-Spreading Network Genetic Algorithm Epidemic Model Stochastic process |
| Content Type | Text |
| Resource Type | Article |
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