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

Takayuki Mizuno,Takaaki Ohnishi,Tsutomu Watanabe

doi:10.1007/s00354-021-00139-x

Abstract

We visualize the rates of stay-home for residents by region using the difference between day-time and night-time populations to detect residential areas, and then observing the numbers of people leaving residential areas. There are issues with measuring stay-home rates by observing numbers of people visiting downtown areas, such as central urban shopping centers and major train stations. The first is that we cannot eliminate the possibility that people will avoid areas being observed and go to other areas. The second is that for people visiting downtown areas, we cannot know where they reside. These issues can be resolved if we quantify the degree of stay-home using the number of people leaving residential areas. There are significant differences in stay-home levels by region throughout Japan. By this visualization, residents of each region can see whether their level of stay-home is adequate or not, and this can provide incentive toward compliance suited to the residents of the region.

Highlights

The coronavirus disease that began at end of 2019 in Wuhan, China, expanded around the world in the blink of an eye, and as of December 8, 2020, more than 67.47 million people around the world have been infected, and approximately 1.54 million have lost their lives
In “Definition of Stay-Home Rate”, the differences between night-time and day-time populations are used to estimate the number of people going out, and we propose a method for computing the rates of stay-home for residents of a region, by correcting for weekly cycles and comparing with values during ordinary times
We visualized the rates of stay-home for residents by region using the difference between day-time and night-time populations to detect residential areas, and observing the numbers of people leaving residential areas

Summary

Introduction

The coronavirus disease that began at end of 2019 in Wuhan, China, expanded around the world in the blink of an eye, and as of December 8, 2020, more than 67.47 million people around the world have been infected, and approximately 1.54 million have lost their lives. In “Definition of Stay-Home Rate”, the differences between night-time and day-time populations are used to estimate the number of people going out, and we propose a method for computing the rates of stay-home for residents of a region, by correcting for weekly cycles and comparing with values during ordinary times.

Results

Conclusion