  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 investigate the
correlations among different time series. It found that the recovery of taxi
demand is not only related to the pandemic severity but strongly correlated
with vaccination progress. Then, the leading and lagging relationship between
vaccination progress and taxi demand is investigated by Time Lagging
Cross-Correlation method. Taxi demand starts to recover after the first-dose
vaccination period started and before the second-dose vaccination period.
However, it was not until mid-April that the recovery rate of taxi demand
exceeded the growth of the vaccination rate.
