How did mobility choices evolve in the first year of the COVID-19 pandemic? Identifying the factors affecting mobility choices: A case study in New York City

This study aims to identify the factors affecting mobility choices (e.g., transit, car, walk) during COVID-19 in New York City. Even though the COVID-19 pandemic evolved over time, most of the current studies heavily relied on cross-sectional datasets to understand individuals' mobility choices. To address this gap, this study uses time-series and panel datasets and estimated aggregate and disaggregate level models to assess individuals' mobility choices. The time-series model result reveals a negative correlation between public transit demand and grocery stores and residential activities during the pandemic. Also, walking demand increases with increased trips to transit stations, retail and recreational areas, and parks. The econometric model results show that employment status, reduced hours or pay cuts at the workplace, income, age, race, family size, and vehicle ownership are the factors that affect individuals' mode-switching behavior during the pandemic. These models can be used for forecasting purposes in the post-pandemic era.