Evidence map›Paper›PMID 41477626›Full record

ArticleWellcome open research2025

Enabling genomic surveillance from 30 years of linked English sentinel network data: The Wellcome Quinquagenarian (QQG) Biomedical Resource.

Simon de Lusignan, Praveen SebastianPillai, Omid Parvizi, Cecilia Okusi, Mark Joy, Shuma Banik, Fatima Batool, Katja Hoschler, Beatrix Kele, Angie Lackenby and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Wellcome open research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

15 authors.

Simon de LusignanNuffield Department of Primary Health Care, University of Oxford, Oxford, Oxforshire, OX2 6GG, UK.ORCID https://orcid.org/0000-0002-8553-2641
Praveen SebastianPillaiRespiratory Virus Unit, UK Health Security Agency, London, UK.
Omid ParviziNuffield Department of Primary Health Care, University of Oxford, Oxford, Oxforshire, OX2 6GG, UK.
Cecilia OkusiNuffield Department of Primary Health Care, University of Oxford, Oxford, Oxforshire, OX2 6GG, UK.ORCID https://orcid.org/0000-0002-5575-8527
Mark JoyNuffield Department of Primary Health Care, University of Oxford, Oxford, Oxforshire, OX2 6GG, UK.
Shuma BanikNuffield Department of Primary Health Care, University of Oxford, Oxford, Oxforshire, OX2 6GG, UK.ORCID https://orcid.org/0009-0004-3153-2461
Fatima BatoolNuffield Department of Primary Health Care, University of Oxford, Oxford, Oxforshire, OX2 6GG, UK.
Katja HoschlerRespiratory Virus Unit, UK Health Security Agency, London, UK.
Beatrix KeleRespiratory Virus Unit, UK Health Security Agency, London, UK.ORCID https://orcid.org/0000-0003-1273-7299
Angie LackenbyRespiratory Virus Unit, UK Health Security Agency, London, UK.
Joanna EllisRespiratory Virus Unit, UK Health Security Agency, London, UK.
Richard PebodyUnited Kingdom Health Security Agency, London, UK.
Conall WatsonImmunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, London, UK.
Jamie Lopez BernalImmunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, London, UK.
Maria ZambonRespiratory Virus Unit, UK Health Security Agency, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The World Health Organisation recommends integrating viral genome sequences and sentinel surveillance data. We report progress in linking clinical, virology, and sequence data to enable genomic surveillance of influenza, respiratory syncytial virus (RSV), and severe-acute-respiratory-syndrome coronavirus-2 (SARS-CoV-2). Methods: We linked individual-level clinical data from the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) sentinel network to virology results from the UK Health Security Agency (UKHSA) reference virology laboratory. We identify where publicly accessible repositories, the Global Initiative on Sharing All Influenza Data (GISAID), or others hold viral genome sequence data from test-positive cases. Our metadata also identifies test-negative controls contemporaneous to test-positive cases. We summarise the scope of data availability in the Wellcome Quinquagenarian (QQG) biomedical resource. Results: We report respiratory virus sampling for influenza, RSV, and SARS-CoV-2 between 1992 and 2023. Samples were collected from a nationally representative subset of RSC general practices participating in the virological surveillance programme.QQG contains 13,665 positive influenza samples, 3,791 positive RSV samples, and 5,068 positive SARS-CoV2 samples. There were 2,819 sequenced influenza genomes, of which 97.1% were linked to clinical records, 1,251 sequenced RSV genomes of which 96.8 were linked to clinical records, and 2,486 sequenced SARS-CoV-2 genomes of which 98.9% were linked to clinical records. Conclusion: We have described the scale of QQG, created to enable genomic surveillance linked to clinical metadata to facilitate research on the impact of different viral variants on clinical outcomes, vaccine effectiveness, and therapeutic strategies.

Indexed as

Feasibility StudiesGeneral PractitionersGenetic CodeGenomicsH1N1H3N2 Subtype SubtypeHealth CareInfluenzaInfluenza AMetadataOutcome AssessmentPrimary Health CareRespiratory Syncytial Viruses RSV respiratory VirusSARS-CoV-2United KingdomVaccine EfficacyVaccines

Identifiers

PMID41477626
PMCPMC12749565

What Socratic 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 Socratic graph.