Evidence map›Paper›PMID 38455312›Full record

ArticleFrontiers in epidemiology2022

Potential Application of SARS-CoV-2 Rapid Antigen Diagnostic Tests for the Detection of Infectious Individuals Attending Mass Gatherings - A Simulation Study.

Conor G McAloon, Darren Dahly, Cathal Walsh, Patrick Wall, Breda Smyth, Simon J More, Conor Teljeur

Open access · diamondAbstract read
In one paragraph

Article in Frontiers in epidemiology, 2022. 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
0.3field-weighted citation impact, top 45% of its field
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, 3 citations in OpenAlex.

  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

7 authors at 5 institutions in 1 country.

Conor G McAloonSchool of Veterinary Medicine, University College Dublin, Dublin, Ireland.
Darren DahlySchool of Public Health, University College Cork, Cork, Ireland.
Cathal WalshDepartment of Mathematics and Statistics, University of Limerick, Limerick, Ireland.
Patrick WallSchool of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland.
Breda SmythDepartment of Public Health, Health Service Executive West, Galway, Ireland.
Simon J MoreSchool of Veterinary Medicine, University College Dublin, Dublin, Ireland.
Conor TeljeurHealth Information and Quality Authority, George's Court, Dublin, Ireland.
University College Dublin · IEHealth Information and Quality AuthorityHealth Service Executive · IEUniversity College Cork · IEUniversity of Limerick · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid Antigen Diagnostic Tests (RADTs) for the detection of SARS-CoV-2 offer advantages in that they are cheaper and faster than currently used PCR tests but have reduced sensitivity and specificity. One potential application of RADTs is to facilitate gatherings of individuals, through testing of attendees at the point of, or immediately prior to entry at a venue. Understanding the baseline risk in the tested population is of particular importance when evaluating the utility of applying diagnostic tests for screening purposes. We used incidence data from January and from July-August 2021, periods of relatively high and low levels of infection, to estimate the prevalence of infectious individuals in the community at particular time points and simulated mass gatherings by sampling from a series of age cohorts. Nine different illustrative scenarios were simulated, small (

Indexed as

COVID-19predictive valueprevalencerapid antigen testSARS-CoV-2

Identifiers

PMID38455312
PMCPMC10911017
OpenAlexW4224325187

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.