Understanding epidemic spread patterns: a visual analysis approach

Junqi Wu, Zhibin Niu*, Xiufeng Liu

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review


Epidemics present significant challenges for public health policy globally, but current tools for visualizing and analyzing epidemic spread are limited, especially at a large scale. This paper presents a novel visual analysis approach for exploring and comparing pandemic patterns in spatial and temporal dimensions across various regions. The method incorporates a potential flow technique to model the spatiotemporal dynamics of epidemics and a visual exploration tool, EPViz, for interactive data analysis. Utilizing COVID-19 data from Illinois and Pennsylvania in the United States, the paper evaluates the method and tool’s effectiveness. These states were chosen for their differing epidemic scenarios and policies. Additionally, interviews with public health policy experts were conducted to gather feedback on the approach and EPViz’s effectiveness, design, and usability. The findings indicate that this new approach and tool enhance expert understanding, support decision-making, and can inform effective strategies for epidemic prevention and control.

Original languageEnglish
JournalHealth Systems
Publication statusAccepted/In press - 2024


  • COVID-19
  • EPViz
  • potential flow method
  • public health policy
  • visual analysis


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