Evidence map›Paper›PMID 40752506›Full record

Observational studyThe Lancet. Microbe2025

SARS-CoV-2 genomic diversity and within-host evolution in individuals with persistent infection in the UK: an observational, longitudinal, population-based surveillance study.

Mahan Ghafari, Steven A Kemp, Matthew Hall, Joseph Clarke, Luca Ferretti, Laura Thomson, Ruth Studley, COVID-19 Infection Survey Group, COVID-19 Genomics UK (COG-UK) Consortium, Ann Sarah Walker and 2 more

Abstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in The Lancet. Microbe, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. The other immune landscape of SARS-CoV-2 evolution.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Review
  3. Article
  4. bronko: ultrafast, alignment-free detection of viral genome variation.bioRxiv : the preprint server for biology · 2026
    Article
  5. Article
  6. 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

12 authors.

Mahan GhafariPandemic Sciences Institute, University of Oxford, Oxford, UK; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK. Electronic address: mahan.ghafari@ndm.ox.ac.uk.
Steven A KempPandemic Sciences Institute, University of Oxford, Oxford, UK; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Matthew HallPandemic Sciences Institute, University of Oxford, Oxford, UK; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Joseph ClarkeBig Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Luca FerrettiPandemic Sciences Institute, University of Oxford, Oxford, UK; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Laura ThomsonPandemic Sciences Institute, University of Oxford, Oxford, UK; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Ruth StudleyOffice for National Statistics, Newport, UK.
COVID-19 Infection Survey Group
COVID-19 Genomics UK (COG-UK) Consortium
Ann Sarah WalkerNuffield Department of Medicine, University of Oxford, Oxford, UK; NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford, Oxford, UK; NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK.
Tanya GolubchikBig Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK; The Sydney Infectious Diseases Institute (Sydney ID), School of Medical Sciences, University of Sydney, Sydney, NSW, Australia.
Katrina LythgoePandemic Sciences Institute, University of Oxford, Oxford, UK; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK; Department of Biology, University of Oxford, Oxford, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPersistent SARS-CoV-2 infections in hospitalised immunocompromised individuals are known to facilitate accelerated within-host viral evolution, potentially contributing to the emergence of highly divergent variants. However, little is known about the evolutionary dynamics and transmission risks of persistent infections in the general population. We aimed to characterise the within-host evolution of SARS-CoV-2 during persistent infections identified through a large community surveillance study.

methodsWe used data from the Office for National Statistics COVID-19 Infection Survey (ONS-CIS), a large-scale, longitudinal, population-based surveillance study conducted in the UK from April, 2020, to March, 2023. For this analysis, we focused on infections with high viral load (cycle threshold ≤30) and available genome sequences, from seven major SARS-CoV-2 lineages (alpha, delta, BA.1, BA.2, BA.4, BA.5, and XBB). ONS-CIS participants were randomly selected from the general population and tested regularly by RT-PCR, regardless of symptoms. We defined persistent infections as those with sustained or rebounding high viral RNA titres for 26 days or longer. We examined associated host characteristics and used raw sequence data to identify de novo mutations and estimate within-host synonymous and non-synonymous evolutionary rates across the SARS-CoV-2 genome.

findingsBetween Nov 2, 2020, and March 21, 2023, we identified 576 persistent infections with at least two sequences, including 11 alpha, 106 delta, 102 BA.1, 204 BA.2, 16 BA.4, 133 BA.5, and 4 XBB. Persistent infections were more common in males than females (p<0·0001) and individuals older than 60 years (p=0·0027). The median within-host genome-wide evolutionary rate was 7·9 × 10

interpretationThis study highlights the heterogeneous nature of within-host SARS-CoV-2 evolution in individuals with persistent infection in the community. Notably, a small subset of persistent infections with high viral loads underwent accelerated viral evolution or recurrently acquired hallmark mutations found in novel variants. In addition, onward transmission from a persistent infection during the later stages of infection is likely to be rare. These insights have important implications for prioritising genomic surveillance and managing patients with persistent infections.

fundingDepartment of Health and Social Care.

Indexed as

COVID-19Genome, ViralSARS-CoV-2AdolescentAdultAgedAged, 80 and overChildEvolution, MolecularFemaleGenetic VariationHumansLongitudinal StudiesMaleMiddle AgedMutation

Identifiers

PMID40752506
PMCPMC7618859

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.