Epidemic Data Visualization Surveillance Based on Flask

ABSTRACT

With the spread of the epidemic, the development of digital industry will be rapidly enhanced in the new situation and opportunities. The combination of mathematical model and graph makes it possible to predict the trend of infectious diseases according to the different transmission speed, spatial scope, transmission route diversity, dynamic mechanism and other factors. The visualization technology of infectious disease model data also plays an important role in epidemic data detection. In this paper, real-time monitoring, quantitative analysis, dynamic prediction and assessment of the current severe situation of the COVID-19 epidemic were conducted to obtain relevant information on the development of the epidemic, objectively estimate the current situation of the COVID-19 epidemic, and predict the development trend in the future. The innovative drag-and-drop recalculation, data viewing, distance roaming and other functions in this paper have greatly improved user experience and enabled users to have the ability of data mining and integration. It provides a one-stop solution, which is from the template, ORM, Session and the Authentication background. It is very convenient to use. The monitoring and trend prediction platform has also naturally become a powerful helper for the government to realize comprehensive monitoring and decision-making on COVID-19. © 2022 IEEE.