Statistical Analysis Of Prediction Model And Applicability Based On COVID-19

Since the outbreak of the COVID-19 in late 2019,it has lasted for more than two years.Exploring the global development process of the epidemic,it is found that the performance of Italy is not satisfactory,the epidemic is difficult to control,and there is a continuous development trend.This thesis analyzes the impact of the Italian epidemic on different aspects of social development based on the obtained data.Then it established a variety of prediction models in order to infer the development trend of the Italian epidemic and explore the characteristics and applicable scenarios of each model.Finally,this thesis puts forward targeted epidemic prevention and control suggestions based on the results of the prediction model and the impact of the epidemic.In chapter 1,it is the introductory part of this thesis,which mainly explains the research background,significance and research status of the new crown pneumonia epidemic at home and abroad,and also introduces the research process and steps of this thesis.In chapter 2,it studies the current situation of the Italian epidemic.The impact of the Italian epidemic on four aspects of different regions,people of different ages,different industries and employment was analyzed separately,and a line chart was drawn based on the number of confirmed cases and deaths in Italy,and a preliminary analysis of the data was carried out.In chapter 3,it mainly uses multiple predictive models to study the outbreak in Italy,include Logistic model,infectious disease dynamics model,autoregressive integrated moving average model and its improved seasonal autoregressive integrated moving average model and long shortterm memory neural network model.The Python programming software was used to realize the prediction simulation of each model for the Italian epidemic,and analyze the applicability of each model according to the prediction results.In chapter 4,it puts forward suggestions on the prevention and control of the Italian epidemic.First,the applicable scenarios of the models are determined according to the characteristics of each model,and then targeted epidemic prevention and control measures are proposed according to the impact of the epidemic on different aspects of Italy.In chapter 5,it summarizes and discusses the thesis,reflects on the shortcomings,proposes improvement and optimization schemes for related problems,and further looks forward to future related research.This thesis studies the applicability of various models to epidemic prediction,and puts forward targeted suggestions.At the same time,the methods and contents in this thesis also have reference significance for epidemic research in other regions of the world.