Evidence map›Paper›PMID 35589453›Full record

ArticleVaccine2022

Identifying immunity gaps for measles using Belgian serial serology data.

Julie Schenk, Steven Abrams, Amber Litzroth, Laura Cornelissen, Tine Grammens, Heidi Theeten, Niel Hens

Abstract read
In one paragraph

Article in Vaccine, 2022. 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.

  1. Informing quarantine policy for measles control in primary school and daycare settings: insights from a simulation study, Flanders, Belgium.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2026
    Article
  2. Cross-sectional seroprevalence study of measles antibodies among children to identify gaps in population immunity, Ireland, 2024.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2026
    Article
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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

7 authors.

Julie SchenkData Science Institute, Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), UHasselt, Diepenbeek, Belgium. Electronic address: julie.schenk@uhasselt.be.
Steven AbramsData Science Institute, Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), UHasselt, Diepenbeek, Belgium; Global Health Institute (GHI), Family Medicine and Population Health (FAMPOP), University of Antwerp, Wilrijk, Belgium.
Amber LitzrothService of Epidemiology of Infectious Diseases, Scientific Directorate of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Laura CornelissenService of Epidemiology of Infectious Diseases, Scientific Directorate of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Tine GrammensService of Epidemiology of Infectious Diseases, Scientific Directorate of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Heidi TheetenCentre for Evaluation of Vaccination (CEV), Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium; Public Health and Surveillance Department, Zorg en Gezondheid Vlaanderen, Belgium.
Niel HensData Science Institute, Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), UHasselt, Diepenbeek, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vaccine-preventable diseases, such as measles, have been re-emerging in countries with moderate to high vaccine uptake. It is increasingly important to identify and close immunity gaps and increase coverage of routine childhood vaccinations, including two doses of the measles-mumps-rubella vaccine (MMR). Here, we present a simple cohort model relying on a Bayesian approach to evaluate the evolution of measles seroprevalence in Belgium using the three most recent cross-sectional serological survey data collections (2002, 2006 and 2013) and information regarding vaccine properties. We find measles seroprevalence profiles to be similar for the different regions in Belgium. These profiles exhibit a drop in seroprevalence in birth cohorts that were offered vaccination at suboptimal coverages in the first years after routine vaccination has been started up. This immunity gap is observed across all cross-sectional survey years, although it is more pronounced in survey year 2013. At present, the COVID-19 pandemic could negatively impact the immunization coverage worldwide, thereby increasing the need for additional immunization programs in groups of children that are impacted by this. Therefore, it is now even more important to identify existing immunity gaps and to sustain and reach vaccine-derived measles immunity goals.

Indexed as

COVID-19MeaslesMumpsRubellaBayes TheoremBelgiumChildCross-Sectional StudiesHumansMeasles-Mumps-Rubella VaccinePandemicsSeroepidemiologic StudiesVaccinationMeasles-Mumps-Rubella VaccineBayesian MCMCImmunity goalsMeasles eliminationSerial serological survey data

Identifiers

PMID35589453
PMCPMC9108896

What OpenQuestion holds

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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.