Examining spatial inequality in COVID-19 positivity rates across New York City ZIP codes
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...
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Veröffentlicht in: | Health & place 2021-05, Vol.69, p.102574-102574, Article 102574 |
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Sprache: | eng |
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Zusammenfassung: | 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.
•Racial/ethnic minority groups are positively related to COVID-19 positivity rates.•Socioeconomic differences cannot explain spatial inequalities in positivity rates.•Remote workers, older adults and household size elevate COVID-19 positivity rates.•Strong spatially structured effects in Brooklyn underscore the importance of space. |
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ISSN: | 1353-8292 1873-2054 |
DOI: | 10.1016/j.healthplace.2021.102574 |