Revealing Spatial-temporal Taxi Demand Patterns after Vaccination in COVID-19 Pandemic
Zihao Li, Cheng Zhang, Xiaoqiang Kong, Yunlong Zhang, Chaolun Ma

TL;DR
This study analyzes how COVID-19 vaccination influences spatial-temporal taxi demand patterns in Chicago, revealing demand recovery correlates with vaccination progress and varies across different city areas.
Contribution
It introduces a multi-source time-series analysis of taxi demand recovery post-vaccination, highlighting spatial differences and the relationship with pandemic severity and vaccination stages.
Findings
Taxi demand increased after vaccination in most areas.
Demand recovery is faster near airports and downtown.
Demand correlates strongly with vaccination progress.
Abstract
The COVID-19 pandemic has had an unprecedented impact on our daily lives. With the increase in vaccination rate, normalcy gradually returns, so is the taxi demand. However, the changes in the spatial-temporal taxi demand pattern and factors impacting the recovery of this demand after COVID-19 vaccination started remain unclear. With the multisource time-series data from Chicago, including pandemic severity, vaccination progress and taxi trip volume, the recovery pattern of taxi demand is analyzed. The result reveals the taxi trip volume and average travel distance increased in most community areas in the city of Chicago after taking the COVID-19 vaccine. Taxi demand recovers relatively faster in the airport and area near the central downtown than in other areas in Chicago. Considering the asynchrony of data, the Pearson coefficient and Dynamic Time Warping (DTW) are both applied to…
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Taxonomy
TopicsCOVID-19 epidemiological studies · Urban Transport and Accessibility · Traffic and Road Safety
