Mobility during the COVID-19 Pandemic: A Data-Driven Time-Geographic Analysis of Health-Induced Mobility Changes

Abstract

The COVID-19 pandemic has profoundly affected the spatial mobility of a major part of the population in many countries. For most people, this was an extremely disruptive shock, resulting in loss of income, social contact and quality of life. However, forced to reduce human physical interaction, most businesses, individuals and households developed new action lines and routines, and were gradually learning to adapt to the new reality. Some of these changes might result in long-term changes in opportunity structures and in spatial preferences for working, employment or residential location choice, and for mobility behavior. In this paper we aim to extend the time-geographic approach to analyzing people’s spatial activities, by focusing on health-related geographical mobility patterns during the pandemic in Sweden. Starting from a micro-approach at individual level and then looking at an aggregate urban scale, we examine the space-time geography during the coronavirus pandemic, using Hägerstrand’s time-geography model. We utilize a massive but (location-wise) fuzzy dataset to analyze aggregate spatiotemporal impacts of the COVID-19 pandemic using a contemporary time-geographical approach. First, we address micro-level behavior in time-space to understand the mechanisms of change and to illustrate that a temporal drastic change in human mobility seems to be plausible. Then we analyze the changes in individuals’ mobility by analyzing their activity spaces in aggregate using mobile phone network data records. Clearly, it is too early for predicting long-term spatial changes, but a clear heterogeneity in spatial behavior can already be detected. It seems plausible that the corona pandemic may have long-lasting effects on employment centers, city roles and spatial mobility patterns.

What drives the changes in public transport use in the context of the COVID‐19 pandemic? Highlights from Lyon metropolitan area

“…Finally, it is more than likely that teleworking will have a rebound effect on the mobility of those who do it (Cerqueira, Motte‐Baumvol, Chevallier, & Bonin, 2020 ; Greenworking & Ademe, 2020 ). Furthermore, we can consider that easier teleworking could be accompanied by large‐scale residential relocation to less dense areas (Toger, Kourtit, Nijkamp, & Östh, 2021 ). These residential changes can also impact the use of transport modes (de Abreu e Silva & Melo, 2018 ), notably to the detriment of public transport.…”

Measuring of the COVID-19 Based on Time-Geography

“…These restrictive measures have the same meaning as the three constraints in time geography to a certain extent [ 8 , 9 ]. Similarly, two important tools in time geography—space-time path and space-time prism—can also be used to simulate the spread of the COVID-19 pandemic [ 10 , 11 , 12 , 13 ]. The time-space path is often used to simulate the life trajectory of the coronavirus carrier, which can be used to find close contacts of the virus carrier [ 14 , 15 ].…”

The Effect of Mobility on the Spread of COVID-19 in Light of Regional Differences in the European Union

“…At this turning point, some research suggests that mobility played a significant role in the control of the spread [3,[10][11][12][13][14]. In terms of geographic transportation, the process of new travel habits under the COVID-19 epidemic may lead to long-term changes in mobility behavior [15]. To be more specific, less mobility could be useful for stalling and stemming the spread of COVID-19 [16].…”