Research On Simulation Prediction Of Epidemic Evolution In Multi-dimension

The massive outbreaks of infectious disease can cause significant disruption in the word and society.Therefore,accurately predicting the future of the epidemic is of great significance,which is helpful to guide relevant departments and personnel to develop strategy to control the spread of the infectious diseases.Starting from the macroscopic and microscopic dimensions,two prediction models was built to study the spread of infectious diseases in regions and closed spaces respectively,and the effectiveness of prevention measures was evaluated through simulation models.The main contents of this paper include:(1)From the macro perspective,this paper studied the development of the epidemic at the regional level.Based on the SEIR(Susceptible,Exposed,Infective,Removal)model,three factors including the movement of people across regions,the constraint of the amount of detection reagents and the constraint of the number of hospital beds were taken into account,and then an improved SEIR was established to predict the trend of epidemic.Finally,the data of cases of COVID-19 in Hubei Province was used to verify the validation of the simulation model,and the forecasting results of the model were consistent with reported cases.In order to verify the effectiveness of the model,the parameter "number of infected and detected patient" was selected for hypothesis test.And then,using the above model,two simulation experiments with several values of a parameter were carried out.(2)From the micro perspective,the spread of epidemic in environment such as the shopping malls,hotels and other closed spaces with plenty of people was modeled and studied: the model considered three factors,namely the characteristics of infectious diseases,the direction of pedestrian’s vision and the difference of individual immunity,and studied the influence of three factors on the spread of infectious diseases.The difference of individual immunity refers to different chances of getting infected,which is cased by the gender,age,and the prevention and control measures.Selected the scenario that included the spread of COVID-19 in a large shopping mall within one hour,and then conducted the simulation experiment.The results show that the age of pedestrians and the prevention and control measures case a certain impact on the spread of epidemic: the elderly are more susceptible to infections,and the proportion of infection among the elderly increased from 39% to74% within one hour;The infection rate of pedestrians who wore masks was lower about 40% than those who did not.(3)A management information system of simulated data based on micro simulation model was designed and developed by using Java EE technology and SSM framework.The functions of the management system: to store and record the data outputted by the micro simulation model;to manage the machine learning models.With the continuous inputting and improving of simulation data for different scenarios,the system can be used to predict and analyze the spread of infectious diseases.