Development And Research Of COVID-19 Development Trend Prediction System Based On QSEIR Model

Since December,2019,the epidemic of novel coronavirus pneumonia（covid-19）has continued to spread all over the world.At present,the new coronavirus Omicron st rain is rampant,and the number of infected cases increases rapidly in a short time,disr upting people’s production and life again.The epidemic,which has lasted for thr ee years,has seriously endangered the lives and health of people all over the world,put forward a severe test on the urban governance system,governance capacity and public health system,greatly impacted economic and trade activities,and will have a far-reac hing impact on the future of mankind.World Health Organization director general Tan Desai said that the impact of novel coronavirus will continue for decades.China has al ways adhered to the people first,life first,scientific,accurate and dynamic clearing,dy namic clearing depends on the fast and effective precision prevention and control,Com puter technology can accurately predict the development trend of epidemic spread acco rding to the early epidemic data,so as to provide an important basis for the formulation of epidemic prevention and control policies and response measures.This paper designs and completes a set of covid-19 virus transmission developme nt trend prediction system.The system consists of a front-end visualization module and a back-end computing module.The front-end visualization module is completed by El Ememt-ui+Vue components,written based on Java Script,using Echarts data visualizat ion middleware,combined with various graphics and tables,to intuitively reflect the cu rrent situation and development status of the epidemic.In the back-end calculation mo dule,first preprocess the early epidemic data,and then use the data classification and s ummary,calculate the average value according to the keywords,so as to meet the data needs of the front-end.Based on the known epidemic data,QSEIR model is proposed t o predict the development trend of various epidemic indicators in the future.In this pap er,by adding attenuation function to the infection rate,the infection rate changing with time is obtained by fitting the data.The experimental results show that the mean square deviation of the algorithm on the test set is 0.11,which is better than the traditional SE IR model.It can effectively predict the development trend of epidemic spread,and can also be extended to the prediction of the spread and development of other infectious dis eases.