Subway Data Reveals Communities of Color Carry the Burden of Essential Work and COVID-19
A new study shows there was substantial social distancing inequalities throughout New York City during the COVID-19 pandemic. Researchers at Columbia University Mailman School of Public Health and Boston University School of Public Health report that areas with the lowest individual income and a greater percentage of non-White and/or Hispanic/Latino individuals, used the subway to a greater degree during the pandemic, and the strongest driver of subway use in communities of color was the percent of individuals in essential work. This is one of the first studies to assess the interrelationship between sociodemographic factors, mobility, and COVID-19. Findings are online in the preprint of medRxiv ahead of peer-reviewed publication.
“Our study provides evidence that the most socially disadvantaged and poorest communities are not only at an increased risk for COVID-19 infection, but lack the privilege to fully engage in social distancing interventions, potentially compounding already existing health inequalities,” said co-author Micaela E. Martinez, PhD, assistant professor of environmental health sciences at Columbia Mailman School of Public Health.
The researchers used zip code tabulation area-level and borough-level demographic data and COVID-19 case data as of April 26, and subway swipe data from January 4 to April 11, for Manhattan, Brooklyn, Queens, and the Bronx (the four boroughs with subways). They assessed the relationship between the decline in subway use and the time it took for each New York City borough to end the exponential growth period of COVID-19 cases.
Martinez and colleagues found that New Yorkers were taking the subway 70 percent less than normal by April 11, but changes in subway ridership varied widely. By borough, Manhattan had the greatest and earliest decline in subway ridership, followed by Brooklyn, then Queens, and lastly, the Bronx.
Only 25 percent of workers in the U.S. are estimated to be able to transition to remote work, meaning there is a continued need for essential workers to leave their home and rely on public transportation where riders are sometimes tightly packed in confined spaces, physically unable to space appropriately apart for social distancing. “With essential workers at increased risk of exposure to COVID-19, there is a likelihood of local transmission rising within the community,” observed Martinez.
By April 26, Queens had the highest number of cumulative cases among the four boroughs, with 49,399 positive COVID-19 cases. This was followed by Brooklyn with 43,014 cases, the Bronx with 35,556 cases, and Manhattan with 21,097 cases.
“The results suggest that the ability to stay home during the pandemic has been constrained by socioeconomic status as well as work circumstances,” noted Martinez. “Poorer neighborhoods are not afforded the same reductions in mobility as their higher-income counterparts. Furthermore, lower socioeconomic status neighborhoods have higher COVID-19 burdens, which may be due to inequities in ability to shelter-in-place, and/or due to the plethora of other existing health disparities that increase vulnerability to COVID-19.”
Mayor Bill de Blasio issued stay-at-home guidance on March 22, following a New York State on PAUSE executive order, and while both were extended for the end of May the city continued to see high rates of infection.
“The extended lag time between the dramatic fall in subway ridership and the end of the exponential growth phase for COVID-19 cases is important for future policy, because it demonstrates that if there is a resurgence, and stay-at-home orders are re-issued, then cities can expect to wait a month before reported cases will plateau,” said Martinez.
Co-authors are Reese Sy, Benjamin Rader, and Laura White, Boston University School of Public Health.
This work was supported by NSF RAPID “Transmission and Immunology of COVID-19 in the Pandemic and Post-Pandemic Phase: Real-time Assessment of Social Distancing & Protective Immunity” (2029421); Google, Tides Foundation (TF2003-089662); and National Institutes of Health (DP5OD023100, R01 GM122876).