Evidence map›Paper›PMID 37713471›Full record

ArticleEuropean journal of public health2024

Predicting Covid-19 infection and death rates among E.U. minority populations in the absence of racially disaggregated data through the use of US data comparisons.

Paola Cecchi Dimeglio, Robert E Fullilove, Catherine Cecchi, Yann Cabon, Jessica Rosenberg

Open access · goldAbstract readComparative Study
In one paragraph

Article in European journal of public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 24% of its field
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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

5 authors at 3 institutions in 2 countries.

Paola Cecchi DimeglioHarvard Law School (Center on the Legal Profession) and Harvard Kennedy School (Women and Public Policy), Harvard University, Cambridge, MA, USA.ORCID 0000-0002-9253-7782
Robert E FulliloveDepartment of Sociomedical Sciences and Health Policy and Management, Mailman School of Public Health, Columbia University, New York, NY, USA.
Catherine CecchiSociété Francaise de Sante Publique and Société Francophone Santé Environnement, Montpellier, France.
Yann CabonBehavioral Insights Institute, Cambridge, MA, USA.
Jessica RosenbergDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.
Columbia University · USHarvard University Press · USSociété Francophone d’Arthroscopie · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe E.U.'s lack of racially disaggregated data impedes the formulation of effective interventions, and crises such as Covid-19 may continue to impact minorities more severely. Our predictive model offers insight into the disparate ways in which Covid-19 has likely impacted E.U. minorities and allows for the inference of differences in Covid-19 infection and death rates between E.U. minority and non-minority populations.

methodsData covering Covid-19, social determinants of health and minority status were included from 1 March 2020 to 28 February 2021. A systematic comparison of US and E.U. states enabled the projection of Covid-19 infection and death rates for minorities and non-minorities in E.U. states.

resultsThe model predicted Covid-19 infection rates with 95-100% accuracy for 23 out of 28 E.U. states. Projections for Covid-19 infection and mortality rates among E.U. minority groups illustrate parallel trends to US rates.

conclusionsDisparities in Covid-19 infection and death rates by minority status likely exist in patterns similar to those observed in US data. Policy Implications: Collecting data by race/ethnicity in the E.U. would help document health disparities and craft more targeted health interventions and mitigation strategies.

Indexed as

COVID-19EthnicityEuropean UnionBlack or African AmericanHealth Status DisparitiesHumansMinority GroupsUnited States

Identifiers

PMID37713471
PMCPMC10843944
OpenAlexW4386758598

What OpenQuestion holds

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LicenceCC BY
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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.