Project Summary
The COVID pandemic has caused an unprecedented decline in transit ridership and has also accelerated adoption of policies designed to increase transit ridership. The primary purpose of this project is to use the large changes in mobility patterns caused by the COVID pandemic to learn about the effectiveness of policies designed to increase transit use. We will concentrate on the area served by the Los Angeles Metropolitan Transit Agency (Metro). This area is one of the largest urban areas in the United States and has a very diverse population. The COVID pandemic has had large and differing impacts across Los Angeles, and these impacts range from minor annoyances to losing jobs, family members, and housing. We can assume that those riding transit in Los Angeles for the first year of the pandemic are almost all composed of those who cannot afford any alternatives such as private cars or transportation network company trips. Therefore, any increase in transit ridership observed in response to new policies can be attributed to “choice” riders that are crucial to rebuilding transit ridership.
This project will measure the extent (and geographic locations) of transit ridership increases during the pandemic and relate these changes to changes in public health restrictions, COVID prevalence, and new policies that Metro is planning to increase ridership. We will measure COVID cases and vaccination rates at weekly intervals, and this high frequency will allow us to flexibly model the complex dynamics linking COVID to mobility and transit use. We will supplement our detailed COVID and transit use data with detailed socioeconomic data at the census tract level from the American Community Survey. These data will allow us to identify disadvantaged communities and therefore measure any differential impacts on these communities. Finally, we will use cell-phone location data obtained from Safegraph to measure overall mobility across tens of thousands of points of interest in Los Angeles county. These Safegraph data can be used as a geographically detailed measure of overall economic activity, and they can also show the extent of adherence to COVID restrictions such as stay-at-home orders.
The detailed policy analyses to be done in this project typically require expensive individual-level data and travel diaries. These individual surveys are too costly and slow for evaluating fast-moving events like the COVID pandemic. This project will demonstrate that careful merging of data that is already being collected by transit agencies, public health agencies, and the U.S. Census can be used to get timely and accurate measures of policy impacts. We will work with Metro to make sure that they can continue to update the merged data and use it for continued evaluation of transit-related policies. This project is expected to inform how certain policy initiatives can affect transit’s recovery from the COVID-19 pandemic if transit ridership is to make a full recovery. Our success in this project would be rather vital to transit agencies like Metro to assess the effectiveness of different policy proposals for achieving transit-related goals like improving equity in transportation and increasing bus ridership while indirectly affecting other wider goals such as reducing road congestion and decreasing vehicle emissions.