Evidence map›Paper›PMID 37088854›Full record

ArticleArchives of public health = Archives belges de sante publique2023

Comparing the incidence of SARS-CoV-2 across age groups considering sampling biases - use of testing data of autumn 2021 in Belgium.

Adrien Lajot, Laura Cornelissen, Dieter Van Cauteren, Marjan Meurisse, Ruben Brondeel, Christine Dupont-Gillain

Abstract read
In one paragraph

Article in Archives of public health = Archives belges de sante publique, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Adrien LajotDepartment of Epidemiology and public health, Sciensano, Brussels, Belgium. adrien.lajot@sciensano.be.
Laura CornelissenDepartment of Epidemiology and public health, Sciensano, Brussels, Belgium.
Dieter Van CauterenDepartment of Epidemiology and public health, Sciensano, Brussels, Belgium.
Marjan MeurisseDepartment of Epidemiology and public health, Sciensano, Brussels, Belgium.
Ruben BrondeelDepartment of Epidemiology and public health, Sciensano, Brussels, Belgium.
Christine Dupont-GillainInstitute of Condensed Matter and Nanosciences, Faculty of Bioscience Engineering, UCLouvain, Louvain-la-Neuve, Belgium. christine.dupont@uclouvain.be.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo design efficient mitigation measures against COVID-19, understanding the transmission dynamics between different age groups was crucial. The role of children in the pandemic has been intensely debated and involves both scientific and ethical questions. To design efficient age-targeted non-pharmaceutical interventions (NPI), a good view of the incidence of the different age groups was needed. However, using Belgian testing data to infer real incidence (RI) from observed incidence (OI) or positivity ratio (PR) was not trivial.

methodsBased on Belgian testing data collected during the Delta wave of Autumn 2021, we compared the use of different estimators of RI and analyzed their effect on comparisons between age groups.

resultsWe found that the RI estimator's choice strongly influences the comparison between age groups.

conclusionThe widespread implementation of testing campaigns using representative population samples could help to avoid pitfalls related to the current testing strategy in Belgium and worldwide. This approach would also allow a better comparison of the data from different countries while reducing biases arising from the specificities of each surveillance system.

Indexed as

BelgiumCOVID-19Observed incidencePositivity ratioReal incidenceSelection bias

Identifiers

PMID37088854
PMCPMC10122721

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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.