A STUDY OF THE INFECTIOUS DISEASE WITH INCUBATION PERIOD MODEL BASED ON CELLULAR AUTOMATA

Considering the two measures of vaccination to susceptible population and isolation treatment to infectious population, this study builds a SEIQR - V infectious disease model with incubation period, which is based on the principle of cellular automata. According to the random walking principle, it gets an expanded Moore neighbor. For influenza A (H1N1), BP neural network is used to recognize the quarantine intensity parameters of some countries. Furthermore, according to Cellular Automata's simulation to the number of infections under the different vaccination proportion, the article studies the factors about spreading regularity of infectious diseases. Simultaneously, for different countries, the study proposes a better control strategy suited to the country's vaccination.