Simulation And Modeling Of COVID-19 Pneumonia Transmission

The outbreak of novel coronavirus pneumonia(COVID-19)threatens the health and safety of all mankind.Therefore,controlling the impact of the disease outbreak has become a major challenge.This disease has a prominent feature: in the incubation period and asymptomatic virus carriers can spread the disease.In order to better simulate the transmission process and results of COVID-19 and the influencing factors of virus transmission.Based on the widely used Anylogic(a tool for modeling and simulation of discrete,system dynamics,multi-agent and hybrid systems),this paper uses the system dynamics system and multi-agent system to establish the simulation model of virus propagation,and deeply studies the influence of various factors on the propagation of COVID-19 in macro and micro levels,which has great auxiliary significance for the government to control the whole virus propagation.The main innovative work of the paper includes the following two parts:(1)From a macro perspective,this paper proposes a classic SEIR model based on which the nodes of infectious and asymptomatic infected persons in the incubation period are added.Using the system dynamics simulation system of Analogic,according to the transmission of COVID-19 in different periods,two simulation models are proposed,which can visualize the process of virus transmission,simulate government control measures,and dynamically adjust the influencing factors,Based on the simulation model,an automatic prediction system is established.The validity of the model was verified by using the real data of the initial and current epidemic situation published by the National Health Commission.This model can simulate virus propagation in any real scene by dynamically adjusting parameters.The visual execution process in the model can more clearly observe the virus propagation process.The prediction system can accurately predict the non extreme actual situation with a certain degree of spread,which is of great significance to the government’s control of the whole virus transmission.(2)From the micro point of view,a multi-agent based agent model is proposed,which uses Analog for simulation modeling.Compared with the classical disease transmission model,the agent model is characterized by that an agent can represent a person’s health state transformation,and can model individuals with unique characteristics to describe the virus transmission process in time and space between individuals.The effects of different infection rates and incidence rate among individuals,as well as the spatial movement of individuals,on the transmission of the whole virus were studied.The experimental results show that the simulation provides useful information for reducing the transmission risk of COVID-19.