Dynamic simulation of a SEIQR-V epidemic model based on cellular automata
Xinxin Tan, Shujuan Li, Sisi Liu, Zhiwei Zhao, Lisa L. Huang, Jiatai Gang, ,Portacom NZ Limited, Auckland 1061 · Numerical Algebra Control and Optimization · 2015
A SEIQR-V epidemic model, including the exposure period, is established based on cellular automata. Considerations are made for individual mobility andheterogeneity while introducing measures of vaccinating susceptible populations and quarantining infectious populations. Referencing the random walkcellular 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 effectsof vaccination proportion and quarantine intensity on epidemic propagation are analogue simulated, obtaining their trends of influenceand optimal control strategies are suggested.