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

Xinxin  Tan; Shujuan  Li; Sisi  Liu; Zhiwei  Zhao; Lisa  Huang; Jiatai  Gang

doi:10.3934/naco.2015.5.327

Article Contents

2015, Volume 5, Issue 4: 327-337. Doi: 10.3934/naco.2015.5.327

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

1.
College of Information Engineering, Dalian University, Dalian 116622
2.
College of Environmental and Chemical Engineering, Dalian University, Dalian, 116622
3.
Portacom NZ Limited, Auckland 1061

Received: November 2014

Revised: October 2015

Published: September 2015

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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.

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Mathematics Subject Classification: Primary: 92B02; Secondary: 37F04.

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