感染症 SIR 数理モデルと多変量解析法を融合した COVID-19 感染状況分析法の新提案

Currently, the estimated value of the effective reproduction number (ERN), which is an index for grasping the COVID-19 infection status, is used for important planning and evaluation of infection prevention measures. Since ERN in the Sequential SIR model fluctuates in multiple dimensions due to changes in the surrounding environment, it is difficult to set the appropriate accuracy of the uncertainty region of the estimated data. The challenge in this study is to build a mathematical model of infectious disease according to the characteristics and data characteristics of the infectious disease and select an appropriate estimation method. Highly accurate quantitative research that analyzes the validity of "how infectious diseases prevail" from an academic point of view is the key to prediction and estimation in appropriate infection situation analysis. In this paper, we will apply the "multivariate analysis method (T Method)" that can evaluate important factors related to ERN prediction and estimation and efficiently process multidimensional information, and explore the construction of a new sequential model of infectious diseases. By applying the multivariate analysis method, we will clarify the important factors related to the prediction and estimation of the infection situation and their contributions, and approach the creation of more permanent infection prevention measures.