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Numerical Algebra, Control and Optimization (NACO)
 

Dynamic simulation of a SEIQR-V epidemic model based on cellular automata

Pages: 327 - 337, Volume 5, Issue 4, December 2015      doi:10.3934/naco.2015.5.327

 
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Xinxin Tan - College of Information Engineering, Dalian University, Dalian 116622, China (email)
Shujuan Li - College of Information Engineering, Dalian University, Dalian 116622, China (email)
Sisi Liu - College of Information Engineering, Dalian University, Dalian 116622, China (email)
Zhiwei Zhao - College of Environmental and Chemical Engineering, Dalian University, Dalian, 116622, China (email)
Lisa Huang - Portacom NZ Limited, Auckland 1061, New Zealand (email)
Jiatai Gang - College of Information Engineering, Dalian University, Dalian 116622, China (email)

Abstract: A SEIQR-V epidemic model, including the exposure period, is established based on cellular automata. Considerations are made for individual mobility and heterogeneity while introducing measures of vaccinating susceptible populations and quarantining infectious populations. Referencing the random walk cellular automata and extended Moore neighborhood theories, influenza A(H1N1) is used as example to create a dynamic simulation using Matlab software. The simulated results match real data released by the World Health Organization, indicating the model is valid and effective. On this basis, the effects of vaccination proportion and quarantine intensity on epidemic propagation are analogue simulated, obtaining their trends of influence and optimal control strategies are suggested.

Keywords:  Cellular automata, vaccination proportion, quarantine intensity, dynamic simulation, influenza A(H1N1).
Mathematics Subject Classification:  Primary: 92B02; Secondary: 37F04.

Received: November 2014;      Revised: October 2015;      Available Online: October 2015.

 References