Evidence map›Paper›PMID 35353810›Full record

ArticlePLoS computational biology2022

Inferring age-specific differences in susceptibility to and infectiousness upon SARS-CoV-2 infection based on Belgian social contact data.

Nicolas Franco, Pietro Coletti, Lander Willem, Leonardo Angeli, Adrien Lajot, Steven Abrams, Philippe Beutels, Christel Faes, Niel Hens

Abstract read
In one paragraph

Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

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  5. Polymorphisms in the ACE I/D (Tropical medicine and infectious disease · 2024
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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

9 authors.

Nicolas FrancoData Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics (I-BioStat), UHasselt, Hasselt, Belgium.ORCID 0000-0003-1688-8342
Pietro ColettiData Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics (I-BioStat), UHasselt, Hasselt, Belgium.ORCID 0000-0001-9935-1692
Lander WillemCentre for Health Economic Research and Modelling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.ORCID 0000-0002-9210-1196
Leonardo AngeliData Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics (I-BioStat), UHasselt, Hasselt, Belgium.ORCID 0000-0002-0555-1587
Adrien LajotDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Steven AbramsData Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics (I-BioStat), UHasselt, Hasselt, Belgium.ORCID 0000-0001-7353-9304
Philippe BeutelsCentre for Health Economic Research and Modelling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.ORCID 0000-0001-5034-3595
Christel FaesData Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics (I-BioStat), UHasselt, Hasselt, Belgium.ORCID 0000-0002-1878-9869
Niel HensData Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics (I-BioStat), UHasselt, Hasselt, Belgium.ORCID 0000-0003-1881-0637

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several important aspects related to SARS-CoV-2 transmission are not well known due to a lack of appropriate data. However, mathematical and computational tools can be used to extract part of this information from the available data, like some hidden age-related characteristics. In this paper, we present a method to investigate age-specific differences in transmission parameters related to susceptibility to and infectiousness upon contracting SARS-CoV-2 infection. More specifically, we use panel-based social contact data from diary-based surveys conducted in Belgium combined with the next generation principle to infer the relative incidence and we compare this to real-life incidence data. Comparing these two allows for the estimation of age-specific transmission parameters. Our analysis implies the susceptibility in children to be around half of the susceptibility in adults, and even lower for very young children (preschooler). However, the probability of adults and the elderly to contract the infection is decreasing throughout the vaccination campaign, thereby modifying the picture over time.

Indexed as

COVID-19AdultAgedAge FactorsBelgiumChildChild, PreschoolHumansIncidenceSARS-CoV-2

Identifiers

PMID35353810
PMCPMC9000131

What OpenQuestion holds

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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.