A Visual Analytics Solution for Analyzing and Mining Infectious Disease Data
Daxuan Chen, Tristan S. Dyck, Carson Kai-Sang Leung, Trevor D. Neudorf, L. Zhang · 2024
In this paper, we present a visual analytics solution to analyze and visualize infectious disease data (e.g., COVID-19 data). During the peak of COVID-19 pandemic we observed large jumps in infections, we delve into the link between the COVID-19 related infection rates and population density. We visually discover knowledge like relationships between population density and infection rates in health regions, as well as connections between infection rates and socio-economic characteristics. Evaluation on real-life Canadian COVID-19 data show the practicality of our visual analytics solution-which employs visualization, data mining techniques and statistical analysis-in providing valuable insights into the dynamics of pandemics.