2021
DOI: 10.1016/s0140-6736(21)01908-5
|View full text |Cite
|
Sign up to set email alerts
|

Daily testing for contacts of individuals with SARS-CoV-2 infection and attendance and SARS-CoV-2 transmission in English secondary schools and colleges: an open-label, cluster-randomised trial

Abstract: Background School-based COVID-19 contacts in England have been asked to self-isolate at home, missing key educational opportunities. We trialled daily testing of contacts as an alternative to assess whether this resulted in similar control of transmission, while allowing more school attendance. Methods We did an open-label, cluster-randomised, controlled trial in secondary schools and further education colleges in England. Schools were randomly assigned (1:1) to self-is… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

6
80
0

Year Published

2021
2021
2023
2023

Publication Types

Select...
7
1

Relationship

1
7

Authors

Journals

citations
Cited by 92 publications
(86 citation statements)
references
References 26 publications
6
80
0
Order By: Relevance
“…Young and colleagues 5 found similar numbers of secondary cases identified in the intervention and control schools, with 44 (1•5%) of 2981 asymptomatic contacts in the intervention group and 14 (1•6%) of 886 asymptomatic contacts in the control group testing positive for SARS-CoV-2 (adjusted odds ratio 0•73 [95% CI 0•33-1•61]; p=0•44). Overall, school attendance was not significantly greater in the daily testing group than in the control group.…”
Section: Daily Antigen Testing To Reduce Disruption When Schools Returnmentioning
confidence: 82%
See 1 more Smart Citation
“…Young and colleagues 5 found similar numbers of secondary cases identified in the intervention and control schools, with 44 (1•5%) of 2981 asymptomatic contacts in the intervention group and 14 (1•6%) of 886 asymptomatic contacts in the control group testing positive for SARS-CoV-2 (adjusted odds ratio 0•73 [95% CI 0•33-1•61]; p=0•44). Overall, school attendance was not significantly greater in the daily testing group than in the control group.…”
Section: Daily Antigen Testing To Reduce Disruption When Schools Returnmentioning
confidence: 82%
“…The trial involved 201 schools and was undertaken at a time of moderate community prevalence (7-day incidence 30-180 per 100 000 population across the study) 6 and during the emergence of the SARS-CoV-2 delta (B.1.617.2) variant in England from April 19 to June 27, 2021. 5 Young and colleagues 5 compared the impact of daily antigen lateral flow testing for 7 days with standard 10-day home isolation on school attendance and SARS-CoV-2 transmission among staff and an ethnically diverse group of 11-18-year-old students (about 25% of whom were non-White) who were close contacts of a proven case.…”
Section: Daily Antigen Testing To Reduce Disruption When Schools Returnmentioning
confidence: 99%
“…Improved communications between schools and parents may reduce the uncertainty to some degree. Furthermore, evidence suggests that rates of COVID-19 in school-based contacts are very low [6]. Communication of such findings may alleviate concerns about having to isolate following positive test results.…”
Section: Discussionmentioning
confidence: 99%
“…Data from a randomised trial of daily contact testing (DCT) in schools carried out during a period of high infection rates in the UK suggests that DCT was not inferior to self-isolation for controlling transmission of SARS-CoV-2 within schools [6]. However, if this approach is to be implemented widely, it is critical that we understand the perspective of those who will be delivering and receiving DCT.…”
Section: Introductionmentioning
confidence: 99%
“…In situations where training data technically removes parts of the population data, the relevance of the model to larger populations could be discredited. The inconsistent and incomplete labeling of ethnic, demographic, and other racial information may also affect data quality [247][248][249]. Machine learning algorithms may unexpectedly increase inconsistency by exaggerating the trial of pandemics and improperly notifying resource allocation based upon insufficient or incomplete data instances.…”
Section: Adaptation Challengesmentioning
confidence: 99%