Social inequality and the changing patterns of travel in the pandemic and post-pandemic era

IF 5.7 2区 工程技术 Q1 ECONOMICS Journal of Transport Geography Pub Date : 2024-06-01 DOI:10.1016/j.jtrangeo.2024.103923
Peter Baudains , Arash Kalatian , Charisma F. Choudhury , Ed Manley
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引用次数: 0

Abstract

The COVID-19 pandemic has had an unprecedented impact on mobility patterns resulting in a significant literature investigating travel behaviours over the course of the pandemic. Missing from much existing work on pandemic mobility is an explicit handling of the time-of-day of travel, which in previous literature has been shown to be an important factor in understanding mobility and, importantly, in understanding the impact on transport networks. In this article, we present a novel analysis of anonymised individual daily mobility patterns in the UK over a 30-month period covering the COVID-19 pandemic using privacy-preserving mobile phone GPS data, collected via integration of software development kits (SDKs) into mobile apps. Our analysis is based on time series clustering of mobility profiles at an hourly level of resolution and enables us to characterize five distinct daily mobility patterns. This typology appears remarkably robust over time, albeit with varying levels of each pattern during the course of the study period. We analyse the relative frequency of these patterns in relation to two dimensions of neighbourhood deprivation in England, with a particular focus on understanding mobility post-lockdown and for over a year after the final restrictions were lifted in the UK. Our results show that although overall mobility patterns have largely returned to their pre-pandemic levels, there remain persistent inequalities in relation to ‘traditional commute’, ‘highly mobile’ and ‘out in the evening’ activity patterns. This finding is expected to have important ongoing policy implications.

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社会不平等以及大流行病和大流行病后时代不断变化的旅行模式
COVID-19 大流行对流动模式产生了前所未有的影响,因此有大量文献对大流行期间的旅行行为进行了调查。在有关大流行病流动性的大量现有研究中,缺少对旅行时间的明确处理,而在以前的文献中,旅行时间已被证明是理解流动性的一个重要因素,更重要的是,它是理解对交通网络影响的一个重要因素。在这篇文章中,我们通过将软件开发工具包(SDK)集成到移动应用程序中收集的隐私保护手机 GPS 数据,对英国在 COVID-19 大流行期间 30 个月内的匿名个人日常移动模式进行了新颖的分析。我们的分析是基于每小时分辨率的移动特征的时间序列聚类,使我们能够描述五种不同的日常移动模式。尽管在研究期间每种模式的程度各不相同,但随着时间的推移,这种类型似乎非常稳健。我们分析了这些模式的相对频率与英格兰居民区贫困程度的两个维度之间的关系,尤其侧重于了解英国最终解除限制后一年多的流动情况。我们的研究结果表明,尽管总体流动模式已基本恢复到大流行前的水平,但在 "传统通勤"、"高度流动 "和 "傍晚外出 "的活动模式方面仍存在持续的不平等。预计这一发现将对当前的政策产生重要影响。
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来源期刊
CiteScore
11.50
自引率
11.50%
发文量
197
期刊介绍: A major resurgence has occurred in transport geography in the wake of political and policy changes, huge transport infrastructure projects and responses to urban traffic congestion. The Journal of Transport Geography provides a central focus for developments in this rapidly expanding sub-discipline.
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