Evidence map›Paper›PMID 36334850›Full record

ArticleJournal of theoretical biology2023

Modelling the impact of repeat asymptomatic testing policies for staff on SARS-CoV-2 transmission potential.

Carl A Whitfield, University of Manchester COVID-19 Modelling Group, Ian Hall

Abstract read
In one paragraph

Article in Journal of theoretical biology, 2023. 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. Article
  2. Article
  3. Analysis of the risk and pre-emptive control of viral outbreaks accounting for within-host dynamics: SARS-CoV-2 as a case study.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  4. Pandemic Preparedness among Big Energy Companies: Call to Research and Action.International journal of environmental research and public health · 2023
    Review
  5. 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

3 authors.

Carl A WhitfieldDepartment of Mathematics, University of Manchester, United Kingdom. Electronic address: carl.whitfield@manchester.ac.uk.
University of Manchester COVID-19 Modelling GroupDepartment of Mathematics, University of Manchester, United Kingdom.
Ian HallDepartment of Mathematics, University of Manchester, United Kingdom.

Funding

Department of HealthMedical Research Council MC_PC_19083Medical Research Council MR/V038613/1
6 · The paper itself

Abstract

Repeat asymptomatic testing in order to identify and quarantine infectious individuals has become a widely-used intervention to control SARS-CoV-2 transmission. In some workplaces, and in particular health and social care settings with vulnerable patients, regular asymptomatic testing has been deployed to staff to reduce the likelihood of workplace outbreaks. We have developed a model based on data available in the literature to predict the potential impact of repeat asymptomatic testing on SARS-CoV-2 transmission. The results highlight features that are important to consider when modelling testing interventions, including population heterogeneity of infectiousness and correlation with test-positive probability, as well as adherence behaviours in response to policy. Furthermore, the model based on the reduction in transmission potential presented here can be used to parameterise existing epidemiological models without them having to explicitly simulate the testing process. Overall, we find that even with different model paramterisations, in theory, regular asymptomatic testing is likely to be a highly effective measure to reduce transmission in workplaces, subject to adherence. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

Indexed as

COVID-19SARS-CoV-2Disease OutbreaksHumansPolicyQuarantineAsymptomatic testingCOVID-19Lateral-flow testingSARS-CoV-2Transmission potentialViral loadWorkplace

Identifiers

PMID36334850
PMCPMC9626407

What OpenQuestion holds

Textmetadata
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.