Design And Implementation Of Epidemic Monitoring And Early Warning System Based On SIR Model

Infectious diseases have repeatedly inflicted heavy losses on the safety of human life and property in human history.From smallpox,plague,SARS to the COVID-19 outbreak at the end of 2019,each outbreak of large-scale epidemics has caused immeasurable losses to the normal development of human society.In the long process of fighting against infectious diseases,various methods have been tried to study the spreading law of infectious diseases in order to predict their development trend.Therefore,the dynamic model of infectious diseases came into being.It can build a mathematical model to quantitatively predict the development trend of the epidemic according to the distribution changes of the various states of the population within the population,the transmission rules of infectious diseases and some external environment or human factors.Data sources are indispensable to model prediction.Therefore,it is imperative to develop an epidemic monitoring and early warning system that provides epidemic data entry and data management functions while improving the accuracy of infectious disease dynamic model prediction.In addition,in order to provide users with convenient access to epidemic data,the system should also have the function of visualization of data such as charts and maps.Based on this background and considering the influence of the frequency of people going out on the infection rate,this paper improves the classic SIR infectious disease dynamics model to improve its short-term prediction accuracy.At the same time,in order to give full play to the short-term prediction ability of the model,the paper developed the epidemic monitoring and early warning system,which provided the improved model with high real-time data source and data visualization display function.The design and implementation of the system mainly focus on the following three issues: First,how to improve the SIR infectious disease prediction model to improve its prediction accuracy;Second,how to realize the data entry and display function of the system;Third,how to improve the system’s ability to deal with large-scale data or explosive data in a short time.In order to solve the above problems,the paper carries out the following work.(1)Based on the classic SIR model,this paper studies the influence of the frequency of people going out on the epidemic transmission.Combining bilinear incidence rate with standard incidence rate,a piecewise incidence function is proposed to improve the sensitivity of SIR model to the change of personnel departure rate,and the classical SIR model is optimized.(2)Python is used to simulate the contagion process described by the optimized SIR model.At the same time,the epidemic monitoring and early warning system based on Browser/Server framework is realized by using Java,and the early warning system has the functions of case information input,data management and data visualization display.(3)Hadoop distributed cluster is established to expand the storage space of the early warning system and meet the demand of large-scale data storage and operation of the early warning system.Through programming simulation,the comparison shows that the error sum of squares of the improved model is reduced by 14.97% compared with the classical SIR model.Meanwhile,the epidemic monitoring and early warning system can provide the functions of data input,data management and data visualization display for the improved model.