Research On Spatio-temporal Heterogeneous Infectious Disease Model Based On Cellular Automata Method

Infectious diseases have the characteristics of sudden onset,rapid transmission,and variability,and their infectivity and destructiveness cannot be underestimated.The research on infectious diseases has always been one of the important issues of concern in human society and the scientific field.Many scholars have established differential equation models to model,analyze,and predict virus transmission,but such models lack consideration of individual and spatial factors,such as the uneven distribution of populations and individual heterogeneity.In addition,the 2019 coronavirus disease(COVID-19)is widely spread worldwide,seriously affecting the lives of billions of people worldwide.Compared with existing infectious diseases,the spread of novel coronavirus has new characteristics,and it is impossible to accurately describe the epidemic situation by completely following the past model.Therefore,analyzing the laws of virus transmission and proposing reasonable control strategies has become a research hotspot.In this paper,a spatiotemporal heterogeneous cellular automata(SH-CA)model is proposed by combining the cellular automata method(CA)with classical differential equation models of infectious diseases and introducing the important factor of isolation.The research work of this paper is as follows.(1)The SH-CA model considers many important factors in the actual epidemic situation of COVID-19,including nucleic acid detection cycle,infectivity of incubation period,population mobility,isolation measures,etc.The SH-CA model is a time-phased model that can set different values of parameters such as cure rate,individual mobility probability,individual effective contact number,nucleic acid detection cycle,and mask wearing rate during different periods of evolution.The model also considers the heterogeneity of spatial distribution.These settings help the model to be closer to the reality of COVID-19 and increase the accuracy of the model.(2)Based on the COVID-19 epidemic data reported in March 2022 in Changchun,Jilin Province,this paper completed a realistic simulation experiment of the epidemic using the SH-CA model,and the fitting results were consistent with the actual data in Changchun.The results show that the SH-CA model has good robustness and predictability.(3)Finally,we conducted a sensitivity analysis of the model,using the control variable method to analyze the impact of three factors,namely,mask wearing rate,nucleic acid detection cycle,and individual mobility probability,on the epidemic situation,as well as the impact of different factors combined to provide effective suggestions for decision makers.