4fd9705d-5446-4bc7-891d-3f25ac8a9820.png
more on: mobilitydensity

Exposure density and neighborhood disparities

in COVID-19 infection risk

+ Constantine Kontokosta, Boyeong Hong, Bartosz Bonczak, Arpit Gupta

Abstract

Exposure density and neighborhood disparities in COVID-19 infection risk

PNAS 

March 30, 2021 118 (13) e2021258118

Although there is increasing awareness of disparities in COVID-19 infection risk among vulnerable communities, the effect of behavioral interventions at the scale of individual neighborhoods has not been fully studied. We develop a method to quantify neighborhood activity behaviors at high spatial and temporal resolutions and test whether, and to what extent, behavioral responses to social-distancing policies vary with socioeconomic and demographic characteristics. We define exposure density as a measure of both the localized volume of activity in a defined area and the proportion of activity occurring in distinct land-use types. Using detailed neighborhood data for New York City, we quantify neighborhood exposure density using anonymized smartphone geolocation data over a 3-mo period covering more than 12 million unique devices and rasterize granular land-use information to contextualize observed activity. Next, we analyze disparities in community social distancing by estimating variations in neighborhood activity by land-use type before and after a mandated stay-at-home order. Finally, we evaluate the effects of localized demographic, socioeconomic, and built-environment density characteristics on infection rates and deaths in order to identify disparities in health outcomes related to exposure risk. Our findings demonstrate distinct behavioral patterns across neighborhoods after the stay-at-home order and that these variations in exposure density had a direct and measurable impact on the risk of infection. Notably, we find that an additional 10% reduction in exposure density city-wide could have saved between 1,849 and 4,068 lives during the study period, predominantly in lower-income and minority communities.

 

Read the Paper

Constantine E. Kontokosta, Ph.D., is an Associate Professor of Urban Science and Planning and Director of the Civic Analytics program at the NYU Marron Institute of Urban Management. He also directs the Urban Intelligence Lab and holds cross-appointments at the Center for Urban Science and Progress (CUSP) and the Department of Civil and Urban Engineering at the NYU Tandon School of Engineering, and is affiliated faculty at the NYU Wagner School of Public Service.

Boyeong Hong is a Postdoctoral Associate of Dr. Constantine Kontokosta's Civic Analytics Program at the NYU Marron Institute of Urban Management.

Bartosz Bonczak is a Research Scientist and Lab Manager in the Civic Analytics Program at the NYU Marron Institute.

Arpit Gupta is an Assistant Professor of Finance at New York University Leonard N. Stern School of Business.

Back to top
see comments ()