Neighborhood disparities in COVID-19 outcomes in New York city over the first two waves of the outbreak.

Bayesian hierarchical model COVID-19 pandemic Case fatality ratio Death rate per capita Incidence rate Modified zcta Race/ethnicity socioeconomic factors

Journal

Annals of epidemiology
ISSN: 1873-2585
Titre abrégé: Ann Epidemiol
Pays: United States
ID NLM: 9100013

Informations de publication

Date de publication:
06 2022
Historique:
received: 19 06 2021
revised: 25 01 2022
accepted: 18 04 2022
pubmed: 30 4 2022
medline: 7 6 2022
entrez: 29 4 2022
Statut: ppublish

Résumé

To assess the association of neighborhood demographic and socioeconomic characteristics with COVID-19 incidence and mortality in New York City (NYC) over the first two waves of outbreak. This retrospective study used neighborhood-level data from 177 modified ZIP code tabulation areas in NYC between March 01, 2020 and April 30, 2021. Neighborhoods that were most severely impacted in wave 1 were also more affected in wave 2. Neighborhoods with a higher percentage of seniors (≥75 years), males, Black and Hispanic population, and large-size households had higher incidence rates of COVID-19 in wave 1 but not in wave 2. Neighborhoods with higher percentage of Black and Hispanic population and lower insurance coverage had higher death rate per capita and case fatality ratio in wave 1, and neighborhoods with higher percentage of Black and Asian population had elevated case fatality ratio in wave 2. Median household income was negatively associated with incidence rate and death rate per capita but not associated with case fatality ratio in both waves. Neighborhoods with more seniors had higher death rate and case fatality ratio in both waves. Neighborhood disparities in COVID-19 incidence and mortality across NYC neighborhoods were dynamic during the first two waves of outbreak.

Identifiants

pubmed: 35487451
pii: S1047-2797(22)00058-8
doi: 10.1016/j.annepidem.2022.04.008
pmc: PMC9042413
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

45-52

Subventions

Organisme : NIEHS NIH HHS
ID : R21 ES029668
Pays : United States

Informations de copyright

Copyright © 2022 Elsevier Inc. All rights reserved.

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Auteurs

Xiaobo Zhong (X)

Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY.

Ziqi Zhou (Z)

Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY.

Guohua Li (G)

Department of Anesthesiology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY; Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY.

Muhire H Kwizera (MH)

Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY.

Peter Muennig (P)

Department of Health Policy and Management, Mailman School of Public Health, Columbia University, New York, NY.

Qixuan Chen (Q)

Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY. Electronic address: qc2138@cumc.columbia.edu.

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Classifications MeSH