Dynamic simulation of a SEIQR-V epidemic model based on cellular automata
Xinxin Tan - 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).
Received: November 2014; Revised: October 2015; Available Online: October 2015.