Correlation Analysis And Visualization Based On Measles Data

For a long time,measles is a catastrophic disease for humans,and the age range of its effects is from children to teenagers even adults.Measles is highly contagious and prone to large-scale epidemics in densely populated areas where the vaccine is not available.Through the analysis and analysis of historical data on the incidence and mortality of measles,valuable information has been extracted,which helps to summarize lessons learned from measles prevention and control,as well as programs and methods for dealing with similar diseases.With the rise of data mining technology and the rapid development of data visualization technology,more and more seemingly unrelated and boring data can be displayed and observed in various visual forms,such as dynamic and interactive.More and more conclusions drawn from the analysis of visual trends can be verified with the aid of quantitative values derived from correlation analysis algorithms.In order to visualize the trend analysis,four sets of visualization modules are developed by using a highly interactive Web method and adopting a mature and stable visual presentation framework.They are the map scatter plot module,map thermodynamic module,province analysis module,and multi-parameter analysis module.The correlation between data was comprehensively analyzed from multiple dimensions of time and space,and multiple angles of GDP and medical data.For the quantitative analysis of correlation,the data sources were checked at first,then cleans and integrates the data sets,and completes data preprocessing.Then compare and select the appropriate correlation analysis method.Finally,eight groups of experiments were performed on the overall correlation analysis,the overall weight analysis,the time dimension analysis of each parameter,and the spatial dimension analysis of each parameter,of which three groups were controlled experiments.The whole experiment process is closely related,and the data sources are accurate and reliable.The conclusions obtained are consistent with historical policies and related literature.From visual trend analysis to correlation quantitative analysis,the entire experimental program is scientifically effective and leads to the following conclusions: 1)The incidence and mortality of measles are related to GDP,the number of medical institutions,the number of disease prevention and control centers,and are significant.Negatively related,in which the number of medical institutions has the highest weight.2)After 1965,the incidence and mortality of measles dropped significantly,and there was a regional imbalance.3)After 1978,overall mortality and morbidity remained at a low level,regional imbalances gradually decreased,and finally approached 0.4)When the number of GDP,medical institutions,and disease prevention and control centers reached a certain value,The correlation between the incidence of morbidity and mortality was very weak and the correlation coefficient was almost approached 0.