Abstract

The COVID-19 pandemic has upended how people travel
and how transportation systems function. Travel is down
across all modes in 2020, though the declines on public
transit have been greater and the recovery slower than on
other travel modes, such as private automobiles and “active”
transportation modes like biking and walking. This shift in
travel mode choice away from transit is likely explained at
least in part by would-be riders’ fears of infection during
this communicable disease outbreak because public transit
congregates people in dense and enclosed environments.
To lower the risk of infection and reduce the spread of
COVID-19, transit agencies worldwide have implemented
measures such as route and service modifications,
improved ventilation and air filtration, increased cleaning
and disinfecting, modifications of seating and boarding
protocols to ensure physical distancing, mask-wearing
requirements, and even screening riders for fevers.
The perception that public transit poses an elevated risk
for the transmission and spread of infectious diseases
influences both people’s reluctance to ride and transit
agencies’ various pandemic response measures. But is
this perception merited, and is transit “safe” to ride? Since
the beginning of the COVID-19 pandemic, this question
has been widely debated. But this is a complex issue that
defies a simple “yes” or “no” answer, as it depends on many
factors (such as ambient infection rates) beyond transit
operators’ control. As we found in our review of the public
health literature, the relative infection risk on public transit
depends not only on how transit operators respond, but
also on the particulars of the communicable disease, rider
and employee adherence to public health guidance, the trip
durations and densities of riders on vehicles, as well as the
effectiveness of the broader public health response. Thus,
arguing in the abstract about whether riding transit is safe
or dangerous during a pandemic is a bit like arguing about
the area of a rectangle knowing only the length of one side.

Abstract

Housing prices have increased at an alarming rate: In 2000, the average price of a house in the U.S. was about $212,000; by the end of 2022, it was more than $552,000. Rising housing prices in dense urban areas, in particular, may place significant constraints on the residential location of low-income households and, in so doing, limit their ability to live in neighborhoods with suitable employment. Such dynamics are particularly acute in coastal areas, where limited housing supply amidst high housing demand have pushed up housing prices compared to inland areas. The growing affordable housing crisis has motivated many low-income households of color to seek lower-cost housing in the outer reaches of metropolitan areas, potentially helping to explain recent increases in commute distance. Long-distance commutes can place a heavy time and cost burden on families with the fewest resources; they also can have negative effects on health as well as the environment.

In this study, the research team examined the relationship between housing affordability and commute distance within two adjacent and diverse Southern California metropolitan areas: the Los Angeles-Orange MSA (characterized by higher costs, coastal location, older, more urban) and the Riverside-San Bernardino MSA (marked by lower costs, inland location, newer, more suburban). Drawing on data from the 2015 Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics dataset and the 2017 5-year American Community Survey, our research centers on the role of “jobs-housing fit,” whether the commutes of low-wage workers are shorter in neighborhoods with a higher ratio of low-wage jobs relative to the number of rental units affordable to low-wage workers.