Visualizing Social and Behavior Change due to the Outbreak of COVID-19 Using Mobile Phone Location Data

Area of Science:

• Urban planning
• Public health surveillance
• Geospatial analysis

Background:

• Traditional methods for measuring stay-home rates are flawed.
• Observing downtown populations doesn't reveal residence or account for avoidance.
• Accurate measurement is crucial for effective public health interventions.

Purpose of the Study:

• To develop and visualize a novel method for quantifying regional stay-home rates.
• To address limitations of existing stay-home measurement techniques.
• To provide residents with region-specific data to encourage compliance.

Main Methods:

• Utilizing the difference between day-time and night-time populations to identify residential zones.
• Monitoring the number of individuals departing from these identified residential areas.
• Visualizing stay-home rates across different regions in Japan.

Main Results:

• Significant regional variations in stay-home levels were observed across Japan.
• The new method effectively quantifies stay-home rates by focusing on departures from residential areas.
• Visualizations highlight disparities in compliance between different regions.

Conclusions:

• The proposed method offers a more accurate assessment of stay-home behavior.
• Regional visualization can motivate residents towards adequate stay-home compliance.
• This approach can inform targeted public health strategies based on local adherence levels.