Journal
HEALTH & PLACE
Volume 69, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.healthplace.2021.102574
Keywords
Spatial inequality; Bayesian spatial modeling; New York City; COVID-19
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The study reveals spatial inequality in COVID-19 positivity rates across different areas of New York City, with factors such as racial/ethnic minority groups, percentage of remote workers, older population, and household size playing a role. The strongest spatial effects are clustered in Brooklyn and Manhattan.
We aim to understand the spatial inequality in Coronavirus disease 2019 (COVID-19) positivity rates across New York City (NYC) ZIP codes. Applying Bayesian spatial negative binomial models to a ZIP-code level dataset (N = 177) as of May 31st, 2020, we find that (1) the racial/ethnic minority groups are associated with COVID-19 positivity rates; (2) the percentages of remote workers are negatively associated with positivity rates, whereas older population and household size show a positive association; and (3) while ZIP codes in the Bronx and Queens have higher COVID-19 positivity rates, the strongest spatial effects are clustered in Brooklyn and Manhattan.
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