Evidence map›Paper›PMID 37593357›Full record

ArticlePreventive medicine reports2023

COVID-19 vaccines for children: Racial and ethnic disparities in New York City.

Brian Elbel, Lloyd Heng, Kevin J Konty, Sophia E Day, Michah W Rothbart, Courtney Abrams, David C Lee, Lorna E Thorpe, Amy Ellen Schwartz

Abstract read
In one paragraph

Article in Preventive medicine reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Racial and ethnic disparities in COVID-19 vaccination: a systematic review and meta-analysis.Archives of public health = Archives belges de sante publique · 2025
    Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
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

9 authors.

Brian ElbelDepartment of Population Health, New York University Grossman School of Medicine, New York, NY, USA.
Lloyd HengDepartment of Population Health, New York University Grossman School of Medicine, New York, NY, USA.
Kevin J KontyBureau of School Health, New York City Department of Health and Mental Hygiene, New York, NY, USA.
Sophia E DayBureau of School Health, New York City Department of Health and Mental Hygiene, New York, NY, USA.
Michah W RothbartMaxwell School, Syracuse University, Syracuse, NY, USA.
Courtney AbramsDepartment of Population Health, New York University Grossman School of Medicine, New York, NY, USA.
David C LeeDepartment of Population Health, New York University Grossman School of Medicine, New York, NY, USA.
Lorna E ThorpeDepartment of Population Health, New York University Grossman School of Medicine, New York, NY, USA.
Amy Ellen SchwartzJoseph R. Biden, Jr. School of Public Policy and Administration, University of Delaware, Newark, DE, USA.

Funding

Large-Scale Disruptions and School/Community Resources: Children’s Longitudinal Health and Education Outcomes Using Linked Administrative DataU01NR020443 · NINR · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ELBEL, BRIAN, SCHWARTZ, AMY ELLEN · 2021 to 2025
$3.5M
NINR NIH HHS U01 NR020443
6 · The paper itself

Abstract

Vaccination is an indispensable tool to reduce negative outcomes due to COVID-19. Although COVID-19 disproportionately affected lower income and Black and Hispanic communities, these groups have had lower population-level uptake of vaccines. Using detailed cross-sectional data, we examined racial and ethnic group differences in New York City schoolchildren becoming fully vaccinated (two doses) within 6 months of vaccine eligibility. We matched school enrollment data to vaccination data in the Citywide Immunization Registry, a census of all vaccinations delivered in New York City. We used ordinary least squares regression models to predict fully vaccinated status, with key predictors of race and ethnicity using a variety of different control variables, including residential neighborhood or school fixed effects. We also stratified by borough and by age. The sample included all New York City public school students enrolled during the 2021-2022 school year. Asian students were most likely to be vaccinated and Black and White students least likely. Controlling for student characteristics, particularly residential neighborhood or school attended, diminished some of the race and ethnicity differences. Key differences were also present by borough, both overall and by racial and ethnic groups. In sum, racial and ethnic disparities in children's COVID-19 vaccination were present. Vaccination rates varied by the geographic unit of borough; controlling for neighborhood characteristics diminished some disparities by race and ethnicity. Neighborhood demographics and resources, and the attributes, culture and preferences of those who live there may affect vaccination decisions and could be targets of future efforts to increase vaccination rates.

Indexed as

ChildCOVID-19COVID-19 VaccinesEthnicityNeighborhood CharacteristicsNew York CityRaceStudentsVaccination

Identifiers

PMID37593357
PMCPMC10428028

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.