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Prevalence of persistent SARS-CoV-2 in a large community surveillance study

Author

Listed:
  • Mahan Ghafari

    (University of Oxford
    University of Oxford
    University of Oxford)

  • Matthew Hall

    (University of Oxford
    University of Oxford)

  • Tanya Golubchik

    (University of Oxford
    University of Sydney)

  • Daniel Ayoubkhani

    (Office for National Statistics
    University of Leicester)

  • Thomas House

    (University of Manchester)

  • George MacIntyre-Cockett

    (University of Oxford
    University of Oxford)

  • Helen R. Fryer

    (University of Oxford)

  • Laura Thomson

    (University of Oxford
    University of Oxford)

  • Anel Nurtay

    (University of Oxford)

  • Steven A. Kemp

    (University of Oxford
    University of Oxford
    University of Oxford)

  • Luca Ferretti

    (University of Oxford
    University of Oxford)

  • David Buck

    (University of Oxford)

  • Angie Green

    (University of Oxford)

  • Amy Trebes

    (University of Oxford)

  • Paolo Piazza

    (University of Oxford)

  • Lorne J. Lonie

    (University of Oxford)

  • Ruth Studley

    (Office for National Statistics)

  • Emma Rourke

    (Office for National Statistics)

  • Darren L. Smith

    (Northumbria University
    Northumbria University)

  • Matthew Bashton

    (Northumbria University
    Northumbria University)

  • Andrew Nelson

    (Northumbria University)

  • Matthew Crown

    (Northumbria University
    Northumbria University)

  • Clare McCann

    (Northumbria University)

  • Gregory R. Young

    (Northumbria University
    Northumbria University)

  • Rui Andre Nunes dos Santos

    (Northumbria University)

  • Zack Richards

    (Northumbria University)

  • Mohammad Adnan Tariq

    (Northumbria University)

  • Roberto Cahuantzi

    (Office for National Statistics)

  • Jeff Barrett

    (Wellcome Sanger Institute)

  • Christophe Fraser

    (University of Oxford
    University of Oxford
    University of Oxford
    Wellcome Sanger Institute)

  • David Bonsall

    (University of Oxford
    University of Oxford
    University of Oxford
    Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington)

  • Ann Sarah Walker

    (University of Oxford
    The National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford
    University of Oxford
    UCL)

  • Katrina Lythgoe

    (University of Oxford
    University of Oxford
    University of Oxford)

Abstract

Persistent SARS-CoV-2 infections may act as viral reservoirs that could seed future outbreaks1–5, give rise to highly divergent lineages6–8 and contribute to cases with post-acute COVID-19 sequelae (long COVID)9,10. However, the population prevalence of persistent infections, their viral load kinetics and evolutionary dynamics over the course of infections remain largely unknown. Here, using viral sequence data collected as part of a national infection survey, we identified 381 individuals with SARS-CoV-2 RNA at high titre persisting for at least 30 days, of which 54 had viral RNA persisting at least 60 days. We refer to these as ‘persistent infections’ as available evidence suggests that they represent ongoing viral replication, although the persistence of non-replicating RNA cannot be ruled out in all. Individuals with persistent infection had more than 50% higher odds of self-reporting long COVID than individuals with non-persistent infection. We estimate that 0.1–0.5% of infections may become persistent with typically rebounding high viral loads and last for at least 60 days. In some individuals, we identified many viral amino acid substitutions, indicating periods of strong positive selection, whereas others had no consensus change in the sequences for prolonged periods, consistent with weak selection. Substitutions included mutations that are lineage defining for SARS-CoV-2 variants, at target sites for monoclonal antibodies and/or are commonly found in immunocompromised people11–14. This work has profound implications for understanding and characterizing SARS-CoV-2 infection, epidemiology and evolution.

Suggested Citation

  • Mahan Ghafari & Matthew Hall & Tanya Golubchik & Daniel Ayoubkhani & Thomas House & George MacIntyre-Cockett & Helen R. Fryer & Laura Thomson & Anel Nurtay & Steven A. Kemp & Luca Ferretti & David Buc, 2024. "Prevalence of persistent SARS-CoV-2 in a large community surveillance study," Nature, Nature, vol. 626(8001), pages 1094-1101, February.
  • Handle: RePEc:nat:nature:v:626:y:2024:i:8001:d:10.1038_s41586-024-07029-4
    DOI: 10.1038/s41586-024-07029-4
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    Cited by:

    1. Mark P. Khurana & Jacob Curran-Sebastian & Neil Scheidwasser & Christian Morgenstern & Morten Rasmussen & Jannik Fonager & Marc Stegger & Man-Hung Eric Tang & Jonas L. Juul & Leandro Andrés Escobar-He, 2024. "High-resolution epidemiological landscape from ~290,000 SARS-CoV-2 genomes from Denmark," Nature Communications, Nature, vol. 15(1), pages 1-16, December.

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