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Record W4295367314 · doi:10.7554/elife.78427

Effectiveness of rapid SARS-CoV-2 genome sequencing in supporting infection control for hospital-onset COVID-19 infection: Multicentre, prospective study

2022· article· en· W4295367314 on OpenAlexaff
Oliver Stirrup, James Blackstone, Fiona Mapp, Alyson MacNeil, Monica Panca, Alison Holmes, Nicholas Machin, Gee Yen Shin, Tabitha Mahungu, Kordo Saeed, Tranprit Saluja, Yusri Taha, N. Mahida, Cassie F. Pope, Anu Chawla, Maria-Teresa Cutino-Moguel, Asif U. Tamuri, Rachel Williams, Alistair C. Darby, David L. Robertson, Flavia Flaviani, Eleni Nastouli, Samuel C. Robson, Darren Smith, Matthew Loose, Kenneth G. Laing, Irene M. Monahan, Beatrix Kele, Sam Haldenby, Ryan P. George, Matthew Bashton, Adam A. Witney, Matthew Byott, Francesc Coll, Michael Chapman, Sharon J. Peacock, Joseph Hughes, Gaia Nebbia, David G. Partridge, Matthew Parker, James Price, Sunando Roy, Luke B. Snell, Thushan I. de Silva, Emma C. Thomson, Paul Flowers, Andrew Copas, Judith Breuer

Bibliographic record

VenueeLife · 2022
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsSt. Thomas Hospital
FundersUniversity College London Hospitals NHS Foundation TrustKing's Health PartnersTrinity College DublinMedical Research CouncilLondon School of Hygiene and Tropical MedicineCardiff UniversityResearch EnglandUniversity of GlasgowNational Institute for Health and Care ResearchUniversité de GenèveUniversity of PortsmouthUK Research and InnovationUniversity of CambridgeAcademy of Medical SciencesWellcome Trust
KeywordsMedicineIncidence (geometry)OutbreakInfection controlProspective cohort studyCoronavirus disease 2019 (COVID-19)Emergency medicineTurnaround timeSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Internal medicinePediatricsIntensive care medicineVirologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Background: Viral sequencing of SARS-CoV-2 has been used for outbreak investigation, but there is limited evidence supporting routine use for infection prevention and control (IPC) within hospital settings. Methods: We conducted a prospective non-randomised trial of sequencing at 14 acute UK hospital trusts. Sites each had a 4-week baseline data collection period, followed by intervention periods comprising 8 weeks of ‘rapid’ (<48 hr) and 4 weeks of ‘longer-turnaround’ (5–10 days) sequencing using a sequence reporting tool (SRT). Data were collected on all hospital-onset COVID-19 infections (HOCIs; detected ≥48 hr from admission). The impact of the sequencing intervention on IPC knowledge and actions, and on the incidence of probable/definite hospital-acquired infections (HAIs), was evaluated. Results: A total of 2170 HOCI cases were recorded from October 2020 to April 2021, corresponding to a period of extreme strain on the health service, with sequence reports returned for 650/1320 (49.2%) during intervention phases. We did not detect a statistically significant change in weekly incidence of HAIs in longer-turnaround (incidence rate ratio 1.60, 95% CI 0.85–3.01; p = 0.14) or rapid (0.85, 0.48–1.50; p = 0.54) intervention phases compared to baseline phase. However, IPC practice was changed in 7.8 and 7.4% of all HOCI cases in rapid and longer-turnaround phases, respectively, and 17.2 and 11.6% of cases where the report was returned. In a ‘per-protocol’ sensitivity analysis, there was an impact on IPC actions in 20.7% of HOCI cases when the SRT report was returned within 5 days. Capacity to respond effectively to insights from sequencing was breached in most sites by the volume of cases and limited resources. Conclusions: While we did not demonstrate a direct impact of sequencing on the incidence of nosocomial transmission, our results suggest that sequencing can inform IPC response to HOCIs, particularly when returned within 5 days. Funding: COG-UK is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) (grant code: MC_PC_19027), and Genome Research Limited, operating as the Wellcome Sanger Institute. Clinical trial number: NCT04405934 .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.375
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2022
Admission routes1
Has abstractyes

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