Research on Combating Epidemics based on Differential Equations and Cellular Automata

Abstract

The new crown pneumonia epidemic has swept the world, panic, anxious, and uneasy emotions flowed into the psychology of everyone. This epidemic not only puts many countries in economic crisis, but may also put some small countries in danger of disappearing forever, and even make it impossible for large-scale people to return home. Therefore, the World Health Organization (WHO) and countries around the world need to join hands and work together to further explore ways to effectively control the epidemic. Analyze the relevant data of the four modes of disease (susceptible persons, latent persons, asymptomatic persons, and recovered persons), establish a differential equation model, and combine the results of question 1 to get the trend of the number of asymptomatic infections (present The trend of first rising and then falling) and specific data (it peaked at about 2733 people on the 42nd day after the outbreak; it dropped to 10 people about 70 days after the outbreak; it decreased to 0 at about 80 days). Then we simulated the distribution of asymptomatic infections based on the data reported by the Beijing Municipal Health Commission and combined with the cellular automaton model: the clustering state appeared in the first 10 days, and it gradually dispersed over time, and the distribution became more distributed after about 50 days. Evenly. Finally, it summarizes the applicable fields of this model in life and effective and accurate suggestions for epidemic prevention and risk reduction.