Evidence map›Paper›PMID 38779406›Full record

ArticleVaccine: X2024

Area and individual level analyses of demographic and socio-economic disparities in COVID-19 vaccination uptake in Belgium.

Pierre Hubin, Laura Van den Borre, Toon Braeye, Lisa Cavillot, Matthieu Billuart, Veerle Stouten, Léonore Nasiadka, Elias Vermeiren, Izaak Van Evercooren, Brecht Devleesschauwer and 2 more

Abstract read
In one paragraph

Article in Vaccine: X, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

12 authors.

Pierre HubinDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Laura Van den BorreDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Toon BraeyeDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Lisa CavillotDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Matthieu BilluartDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Veerle StoutenDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Léonore NasiadkaDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Elias VermeirenDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Izaak Van EvercoorenDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Brecht DevleesschauwerDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Lucy CatteauDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Joris A F van LoenhoutDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vaccination has played a major role in overcoming the COVID-19 pandemic. However, vaccination status can be influenced by demographic and socio-economic factors at individual and area level. In the context of the LINK-VACC project, the Belgian vaccine register for the COVID-19 vaccination campaign was linked at individual level with other registers, notably the COVID-19 laboratory test results and demographic and socio-economic variables from the DEMOBEL database. The present article aims at investigating to which extent COVID-19 vaccination status is associated with area level and/or individual level demographic and socio-economic factors. From a sample of all individuals tested for SARS-CoV-2 (LINK-VACC sample) demographic and socio-economic indicators are derived and their impact on vaccination coverages at an aggregated geographical level (municipality) is quantified. The same indicators are calculated for the full Belgian population, allowing to assess the representativeness of the LINK-VACC sample with respect to the impact of demographic and socio-economic disparities on vaccination uptake. In a second step, hierarchical models are fitted to the individual level LINK-VACC data to disentangle the individual and municipality effects allowing to evaluate the added value of the availability of individual level data in this context. The most important effects observed at the individual level are reflected in the aggregated data at the municipality level. Multilevel analyses show that most of the demographic and socio-economic impacts on vaccination are captured at the individual level, although accounting for area level in individual level analyses improve the overall description.

Indexed as

COVID-19 vaccinationHealth inequalitiesMultilevel analysisSocial determinants of health

Identifiers

PMID38779406
PMCPMC11108972

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.