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The lockdown, mobility, and spatial health disparities in COVID-19 pandemic: A case study of New York City.
Huang, Youqin; Li, Rui.
  • Huang Y; Department of Geography and Planning, Center for Social and Demographic Analysis, University at Albany, SUNY, United States of America.
  • Li R; Department of Geography and Planning, University at Albany, SUNY, United States of America.
Cities ; 122: 103549, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1588097
ABSTRACT
The world has adopted unprecedented lockdown as the key method to mitigate COVID-19; yet its effect on pandemic outcomes and health disparities remains largely unknown. Adopting a multilevel conceptual framework, this research investigates how city-level lockdown policy and public transit system shape mobility and thus intra-city health disparities, using New York City as a case study. With a spatial method and multiple sources of data, this research demonstrates the uneven impact of the lockdown policy and public transit system in shaping local pandemic outcomes. Census tracts with people spending more time at home have lower infection and death rates, while those with a higher density of transit stations have higher infection and death rates. Residential profile matters and census tracts with a higher concentration of disadvantaged population, such as Blacks, Hispanics, poor and elderly people, and people with no health insurance, have higher infection and death rates. Spatial analyses identify clusters where the lockdown policy was not effective and census tracts that share similar pandemic characteristics. Through the lens of mobility, this research advances knowledge of health disparities by focusing on institutional causes for health disparities and the role of the government through intervention policy and public transit system.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Case report Language: English Journal: Cities Year: 2022 Document Type: Article Affiliation country: J.cities.2021.103549

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Case report Language: English Journal: Cities Year: 2022 Document Type: Article Affiliation country: J.cities.2021.103549