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

Tan Xin-xin | Zendy; Shujuan Li | Zendy; Sisi Liu | Zendy; Zhiwei Zhao | Zendy; Lisa Huang | Zendy; Jiatai Gang | Zendy

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

Author(s) -

Tan Xin-xin,

Shujuan Li,

Sisi Liu,

Zhiwei Zhao,

Lisa Huang,

Jiatai Gang

Publication year - 2015

Publication title -

numerical algebra control and optimization

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.303

H-Index - 20

eISSN - 2155-3289

pISSN - 2155-3297

DOI - 10.3934/naco.2015.5.327

Subject(s) - cellular automaton , computer science , automaton , epidemic model , stochastic cellular automaton , theoretical computer science , artificial intelligence , sociology , demography , population

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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