City mobility patterns during the COVID-19 pandemic: analysis of a global natural experiment

Abstract

Background

During the COVID-19 pandemic, changes were seen in city mobility patterns around the world, including in active transportation (walking, cycling, micromobility, and public transit use), creating a unique opportunity for global public health lessons and action. We aimed to analyse a global natural experiment exploring city mobility patterns during the pandemic and how they related to the implementation of COVID-19-related policies.

Methods

We obtained data from Apple's Mobility Trends Reports on city mobility indexes for 296 cities from Jan 13, 2020 to Feb 4, 2022. Mobility indexes represented the frequency of Apple Maps queries for driving, walking, and public transit journeys relative to a baseline value of 100 for the pre-pandemic period (defined as Jan 13, 2020). City mobility index trajectories were plotted with stratification by country income level, transportation-related city type, population density, and COVID-19 pandemic severity (SARS-CoV-2 infection rate). We also synthesised global pandemic policies and recovery actions that promoted or restricted city mobility and active transportation (walking, cycling and micromobility, and public transit) using the Shifting Streets dataset. Additionally, a natural experiment on a global scale evaluated the effects of new active transportation policies on walking and public transit use in cities around the world. We used multivariable regression with a difference-in-difference (DID) analysis to explore whether the implementation of walking or public transit promotion policies affected mobility indexes, comparing cities with and without implementation of these policies in the pre-intervention period (Jan 27 to April 12, 2020) and post-intervention period (April 13 to June 28, 2020).

Findings

Based on city mobility index trajectories, we observed an overall decline in mobility indexes for walking, driving, and public transit at the beginning of the pandemic, but these values began to increase in April, 2020. Cities with lower population densities generally had higher driving and walking indexes than cities with higher population density, while cities with higher population densities had higher public transit indexes. Cities with higher pandemic severity generally had higher driving and walking indexes than cities with lower pandemic severity, while cities with lower pandemic severity had higher public transit indexes than other cities. We identified 587 policies in the dataset that had known implementation dates and were relevant to active transportation, which included 305 policies on walking, 321 on cycling and micromobility, and 143 on public transit, across 230 cities within 33 countries (19 high-income, 11 middle-income, and three low-income countries). In the global natural experiment (including 39 cities), implementation of policy interventions promoting walking was significantly associated with a higher absolute value of the walking index (DID coefficient 20·675 [95% CI 8·778–32·572]), whereas no such effect was seen for public transit-promoting policies (0·600 [–13·293 to 14·494]).

Interpretation

Our results suggest that the policies implemented to mitigate the COVID-19 pandemic were effective in changing city mobility patterns, especially increasing active transportation. Given the known benefits of active transportation, such policies could be maintained, expanded, and evaluated post pandemic. The discrepancy in the interventions between countries of different incomes highlights that changes to the infrastructure to prioritise safe walking, cycling, and easy access to public transit use could help with the future-proofing of cities in low-income and middle-income countries.

Funding

None.