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Much of the world has adopted unprecedented lockdown policies as the key method to address the spread of COVID-19; yet their effect on pandemic outcomes remain largely unknown. This research determines how mobility restriction policies and public transit system shape intra-city health disparities in this pandemic, using New York City as a case study. With a spatial method and multiple sources of data, this research demonstrates the effectiveness of the stay-at-home order. On average, people spent about 20% more time at home in 2020 than in the same period in 2019. Census tracts with people spending more time at home have lower infection and death rates, while those with more subway stations and bus stops have higher infection and death rates. Socioeconomic factors also shape pandemic outcomes, and census tracts with a higher concentration of minorities, poor and elderly people, people with no health insurance, and larger and overcrowded households have higher infection and death rates. Geographically Weighted Regressions show their effects vary significantly across space, and high-risk clusters can be identified. Through the lens of mobility, this research advances our knowledge of health disparities by focusing on the institutional and environmental sources of health disparities.
Huang, Youqin and Li, Rui. 2021. "Stay-at-Home Order and Spatial Disparities in COVID-19 Pandemic in New York City" Understanding and eliminating minority health disparities in a 21st-century pandemic: A White Paper Collection. University at Albany, SUNY: Scholars Archive.
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