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Racial disparities in environmental exposures and SARS-CoV-2 infection rates: A detailed population-weighted analysis

  • Wenyan Xu
  • , Bin Jiang*
  • , William C. Sullivan
  • , Chris Webster
  • , Yi Lu
  • , Na Chen
  • , Zhaowu Yu
  • , Bin Chen*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

The COVID-19 pandemic has cast a spotlight on the intersection of socio-economic, demographic, and environmental factors with public health, particularly in the context of SARS-CoV-2 infection rates. A gap remains in understanding how racial disparities in environmental exposure correlate with racial disparities in infection rates. This study bridges this gap by analyzing infection data for black and white populations across 1,416 counties in the contiguous United States, utilizing high-resolution land cover data and racial population maps to assess environmental exposure disparities. We found significant connections between racial disparities in environmental exposure and SARS-CoV-2 infection rates, even after accounting for population density, socio-economic status, and demographic factors. Disparities among black and white population's access to green spaces, such as non-park forests and pasture/hay areas, as well as to developed areas of varying intensities, closely mirror racial disparities in infection rates. Crucially, we found that smaller differences in environmental exposure between races are associated with smaller differences in infection rates. This relationship is most pronounced within a 400-meter radius, underscoring the critical role of proximity in the design of urban and landscape environments to promote public health equity. © 2023 Elsevier Ltd
Original languageEnglish
Article number105135
JournalSustainable Cities and Society
Volume101
Online published16 Dec 2023
DOIs
Publication statusPublished - Feb 2024

Funding

This work was supported by research grants. Bin Jiang and his lab members were supported by University Research Committee of The University of Hong Kong ( 102010054.088616. 01100.302.01 ) and the Research Grants Council of General Research Fund ( 17606621 ). Bin Chen was supported by The University of Hong Kong HKU-100 Scholars Fund, Seed Fund for Strategic Interdisciplinary Research Scheme Fund, the Research Grants Council of Hong Kong Early Career Scheme ( HKU27600222 ) and General Research Fund ( HKU17601423 ), and The University of Hong Kong Faculty of Business and Economics and Shenzhen Research Institutes ( SZRI2023-CRF-04 ). Na Chen was supported by National Natural Science Foundation of China (No. 51908202 ).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 10 - Reduced Inequalities
    SDG 10 Reduced Inequalities
  3. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Research Keywords

  • COVID-19
  • Development intensity
  • Environmental justice
  • Green spaces
  • Racial disparity

RGC Funding Information

  • RGC-funded

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