Epid data explorer: A visualization tool for exploring and comparing spatio-temporal epidemiological data

Area of Science:

• Epidemiology
• Data Science
• Information Visualization

Background:

• Analyzing large spatio-temporal datasets is crucial for epidemiological research.
• Automatic analysis methods require prior knowledge, potentially missing novel insights.
• Information visualization offers hypothesis-free data exploration.

Purpose of the Study:

• Introduce Epid Data Explorer (EDE), a novel visualization tool for spatio-temporal epidemiological data.
• Enable exploration and comparison of epidemiological indicators and trends across space and time.
• Facilitate secure data import for both pre-loaded and user-defined datasets.

Main Methods:

• Development of Epid Data Explorer (EDE), a user-friendly visualization tool.
• Integration of ready-to-use and user-uploaded datasets.
• Secure architecture for data import, ensuring confidentiality.
• Application of EDE to COVID-19 data for use-case analysis.

Main Results:

• EDE facilitates easy comparison of epidemiological indicators and trends across geographical areas and time periods.
• Demonstrated the impact of lockdown measures on mobility using EDE.
• Assessed correlations between COVID-19 spread and weather conditions via EDE.
• Highlighted EDE's capability for hypothesis-free discovery in complex datasets.

Conclusions:

• EDE is an effective tool for exploring complex spatio-temporal epidemiological data.
• Visualization aids in understanding the impact of interventions and environmental factors on disease spread.
• EDE supports both pre-defined and exploratory analysis in epidemiology.