Design And Empirical Study Of Epidemic Model Based On Cellular Automata

Epidemic exist throughout the development of human society,which has always been an important topic of concern.Due to the complexity of its species and has the characteristics of suddenness,autoimmune,infectious,so the research of epidemic has always been a common problem of the medical profession and academics.At present,experts and scholars in the field of medicine have carried out a series of studies on infectious diseases.They mainly start from the pathogen and pathogenesis of epidemic,and develop corresponding vaccines to fight epidemic.In general,vaccines take a long time to develop,and most viruses are mutable.For the sudden outbreak of epidemic,it is far from enough to rely only on medical means to deal with the epidemic situation,the prediction and prevention of epidemic are also very important.In addition,because of ethical issues,clinical studies of infectious diseases do not use blank controlled trials.To solve the above problems,computer simulation provides these possibilities.Using computer to simulate the spread of the epidemic process,not only can do blank controlled experiments,but also can obtain the spread trend of epidemic,which provides theoretical support for the prevention and control of epidemic.There have been a lot of relevant research work,but there are still many shortcomings.For example,many scholars used the traditional epidemic model to study the spread of COVID-19,such as SIR(Susceptible-Infected-Recovered)epidemic model,SEIR(Susceptible-Exposed-Infected-Recovered)epidemic model and other models.Although these models have certain mathematical description ability,they do not fully consider the characteristics of the epidemic situation,so they cannot accurately describe the epidemic situation.In addition,this kind of differential equation model has great limitations,such as they have the tolerance to initial value and boundary,do not have the subjective initiative,and cannot describe the complex random behavior.Additionally,it is necessary to consider some intervention factors of the model,such as the strong isolation and control measures adopted by many countries and regions during the COVID-19 epidemic,and the relevant model research is still lacking.Therefore,the study of epidemic model can be carried out further.To response the above problems,combined with the characteristics of COVID-19 epidemic transmission,this paper carried out the following research work:(1)Based on the principle of Cellular Automata,the SEIRD(Susceptible-ExposedInfected-Recovered-Death)model is proposed.First of all,considering that the death toll of this epidemic can’t be ignored,the death population is introduced based on the traditional SEIR model.Secondly,the latent persons of COVID-19 are infectious and not less than the infectious ability of the infected persons.However,the traditional SEIR model does not take this characteristic into account,so it cannot be accurately described.Therefore,this model considers the factor that the incubation period is infectious.Finally,in order to overcome the problem that traditional differential equation models cannot express the randomness of complex systems,this model combines the principle of cellular automata,which can not only describe the complex random behavior of various populations well,but also directly reflect the epidemic transmission situation in different time steps.Since the intervention and control factors of the epidemic were not taken into account,this model is suitable for simulating the early outbreak stage of COVID-19.(2)Based on the principle of Cellular Automata,the SEIQRD(Susceptible-ExposedInfected-Quarantine-Recovered-Death)model is proposed.In order to describe the middle and late stages of the epidemic,this model takes into account various intervention factors on the basis of the SEIRD model.The factors are mainly divided into two categories: non-drug interventions and drug interventions.On the one hand,the model introduces the population of isolators,and considers the two different isolation cases of latent and infected persons.When isolated,these persons are not mobile and ignore their infection ability.On the other hand,the model incorporates the elements of vaccination,introducing vaccination rates,and it is assumed that vaccinated population acquires permanent immunity.Due to the consideration of intervention factors in the model,this model is suitable for simulating the late outbreak stages of COVID-19.(3)An epidemic simulation system was designed and implemented.In order to facilitate the simulation of the transmission in the early and late stages of the epidemic,a simulation system of epidemic was developed based on the previous two studies.This system can choose two different models: SEIRD and SEIQRD.By setting the model parameters,run and show the visualization process of the simulation of infectious diseases at different stages.In addition,the trend chart of epidemic simulation can also be obtained.(4)Based on the real data of COVID-19,the transmission of COVID-19 in Wuhan was simulated and analyzed.SEIRD and SEIQRD models were used to simulate the early and late stages respectively.In addition,the sensitivity analysis was carried out on the two models respectively,and verified the feasibility of the model.The research results show that the two models proposed in this paper can well describe the transmission of COVID-19 in different stages,which verifies the flexibility and reliability of the models.Moreover,it can be extended to the epidemic simulation of similar epidemic.In general,the work of this paper has important guiding significance for the study of similar epidemic,and it provides technical support for the formulation of prevention and control measures.