Evidence map›Paper›PMID 40514747›Full record

ArticleArchives of public health = Archives belges de sante publique2025

COVID-19 RT-qPCR-based screening in Austrian schools and incidences in the general population: a Bayesian spatiotemporal analysis.

Yessika Adelwin Natalia, Sereina Annik Herzog, Thomas Neyens, Christoph Johann Zurl, Volker Strenger, Geert Molenberghs, Christel Faes

Abstract read
In one paragraph

Article in Archives of public health = Archives belges de sante publique, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yessika Adelwin NataliaI-Biostat, Data Science Institute, Hasselt University, Hasselt, Belgium. yessikaadelwin.natalia@uhasselt.be.
Sereina Annik HerzogInstitute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria.
Thomas NeyensI-Biostat, Data Science Institute, Hasselt University, Hasselt, Belgium.
Christoph Johann ZurlDepartment of Pediatrics and Adolescent Medicine, Medical University of Graz, Graz, Austria.
Volker StrengerDepartment of Pediatrics and Adolescent Medicine, Medical University of Graz, Graz, Austria.
Geert MolenberghsI-Biostat, Data Science Institute, Hasselt University, Hasselt, Belgium.
Christel FaesI-Biostat, Data Science Institute, Hasselt University, Hasselt, Belgium.

Funding

Belgian Science Policy Office TD/231/BE-PIN
6 · The paper itself

Abstract

In 2021, the emergence of highly transmissible COVID-19 variants of concern increased susceptibility among younger populations. Despite this risk, face-to-face education remained essential for societal functioning and children's well-being, prompting the Austrian government to implement a nationwide screening program in educational institutions. This study explores the impact of this program on COVID-19 transmission by examining the relationship between incidence rates and factors such as age, vaccination coverage, and RT-qPCR positivity rates among school-aged children across Austrian districts, using a Bayesian spatiotemporal discrete model. Our findings highlight significant effects of vaccination and positivity rates on COVID-19 incidence, with variations in their influence across different age groups and locations. These results underscore the importance of monitoring these variables, particularly when active screening programs are in place.

Indexed as

AustriaCOVID-19RT-qPCRSchoolScreeningSpatiotemporal analysis

Identifiers

PMID40514747
PMCPMC12164201

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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.