ABSTRACT
The progression of the global COVID-19 epidemic situation is the main focus of attention of all countries in the world. Due to characteristics, such as multi-origins, huge amount, and inaccessibility, of the existing data, an all-round analyzation of the epidemic situation, which is in dire need, is impeded. The aim of the following study is to provide a multi-dimensional analysis of COVID-19 through visualization and dynamic simulation of data. In order to achieve this goal, the study collected related data though multiple platforms and used tools such as Echarts and Java Swing to visualize the data, and then dynamically simulated the transmission model. Moreover, the data of Wuhan has been applied to the SEIR model to study the effect of quarantine on the transmission of COVID-19. Ultimately, the study hopes to demonstrate an effective method of data analyzation that can be applied to prevent and contain similar outbreak in the future. © 2021, Springer Nature Switzerland AG.