Evidence map›Paper›PMID 35487451›Full record

ArticleAnnals of epidemiology2022

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

Xiaobo Zhong, Ziqi Zhou, Guohua Li, Muhire H Kwizera, Peter Muennig, Qixuan Chen

Abstract read
In one paragraph

Article in Annals of epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Assessing New York City's COVID-19 Vaccine Rollout Strategy: A Case for Risk-Informed Distribution.Journal of urban health : bulletin of the New York Academy of Medicine · 2024
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Xiaobo ZhongDepartment of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY.
Ziqi ZhouDepartment of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY.
Guohua LiDepartment 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 KwizeraDepartment of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY.
Peter MuennigDepartment of Health Policy and Management, Mailman School of Public Health, Columbia University, New York, NY.
Qixuan ChenDepartment of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY. Electronic address: qc2138@cumc.columbia.edu.

Funding

Bayesian exposure-response analysis for immunoassays data with measurement errorsR21ES029668 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI CHEN, QIXUAN · 2019 to 2020
$417k
NIEHS NIH HHS R21 ES029668
6 · The paper itself

Abstract

purposeTo 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.

methodsThis retrospective study used neighborhood-level data from 177 modified ZIP code tabulation areas in NYC between March 01, 2020 and April 30, 2021.

resultsNeighborhoods 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.

conclusionsNeighborhood disparities in COVID-19 incidence and mortality across NYC neighborhoods were dynamic during the first two waves of outbreak.

Indexed as

COVID-19Disease OutbreaksHumansMaleNew York CityResidence CharacteristicsRetrospective StudiesSARS-CoV-2Socioeconomic FactorsBayesian hierarchical modelCase fatality ratioCOVID-19 pandemicDeath rate per capitaIncidence rateModified zctaRace/ethnicitysocioeconomic factors

Identifiers

PMID35487451
PMCPMC9042413

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.