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The COVID-19 pandemic is an unprecedented event that has shifted travel patterns. The Toronto Transit Commission witnessed a significant ridership drop and subsequent fluctuations during the pandemic. This exploratory research investigates ridership changes using statistical and spatial analysis over different intervals based on changes in government-imposed restrictions. Ridership increased with the lifting of restrictions, while mixed ridership trends were observed during the intermittent lockdown periods. On the spatial side, relatively high degrees of homogeneity in ridership changes were discovered for census tracts with subway service, and census tracts along subway lines showed heterogeneity. For trips that end downtown, the ridership was cut in half compared to pre-pandemic levels and demonstrated similar change patterns to the trips ending elsewhere. Lastly, some socioeconomic and demographic factors were found to be the driving factors with spatial inherency for positive ridership change using geographic weighted regression models.
Yichun Du (Fri,) studied this question.