Visual Analysis of Epidemic Epidemiological Investigation Track Data

Dan Luo; Yadong Wu; Kai Liu; Weihan Zhang

doi:10.62051/ijcsit.v2n1.48

Authors

Dan Luo
Yadong Wu
Kai Liu
Weihan Zhang

DOI:

https://doi.org/10.62051/ijcsit.v2n1.48

Keywords:

Expectation-Maximization; Epidemiological Survey Data; Visualized Analysis; Trajectory Visualization

Abstract

The visualization analysis of the flow data of the novel coronavirus pneumonia epidemic can intuitively show the development dynamics of the epidemic, explore the law of epidemic transmission, and provide a new way of thinking and method for the analysis of the epidemic situation. Firstly, the convection-modulated trajectory data is preprocessed, and then the convection-modulated data is theoretically transferred on the basis of expectation maximization statistics to realize multi-trajectory fusion algorithm, and finally the trajectory fitting of infected population is carried out. Finally, the multi-type thematic map is used to combine the flow data with the map system to realize the visualization of flow data and conduct in-depth analysis, so as to dig out the distribution characteristics of the flow data, provide a reference for the prevention and control of the novel coronavirus epidemic in a place, enable people to correctly understand the spread of the epidemic, and promote the development of preventive medicine.

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