Ct threshold values, a proxy for viral load in community SARS-CoV-2 cases, demonstrate wide variation across populations and over time

  1. A Sarah Walker
  2. Emma Pritchard
  3. Thomas House
  4. Julie V Robotham
  5. Paul J Birrell
  6. Iain Bell
  7. John I Bell
  8. John N Newton
  9. Jeremy Farrar
  10. Ian Diamond
  11. Ruth Studley
  12. Jodie Hay
  13. Karina-Doris Vihta
  14. Timothy EA Peto
  15. Nicole Stoesser
  16. Philippa C Matthews
  17. David W Eyre
  18. Koen B Pouwels
  19. COVID-19 Infection Survey team

  • Curated by eLife

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    Evaluation Summary:

    The authors present a systematic and complete study of Ct (cycle threshold) values in RT-PCR tests and gene-specific positivity for the UK ONS infection survey. There are very few datasets like this for any viral pathogen, regardless of pandemics. The patterns are fascinating and thought-provoking.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

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Abstract

Information on SARS-CoV-2 in representative community surveillance is limited, particularly cycle threshold (Ct) values (a proxy for viral load).

Methods:

We included all positive nose and throat swabs 26 April 2020 to 13 March 2021 from the UK’s national COVID-19 Infection Survey, tested by RT-PCR for the N, S, and ORF1ab genes. We investigated predictors of median Ct value using quantile regression.

Results:

Of 3,312,159 nose and throat swabs, 27,902 (0.83%) were RT-PCR-positive, 10,317 (37%), 11,012 (40%), and 6550 (23%) for 3, 2, or 1 of the N, S, and ORF1ab genes, respectively, with median Ct = 29.2 (~215 copies/ml; IQR Ct = 21.9–32.8, 14–56,400 copies/ml). Independent predictors of lower Cts (i.e. higher viral load) included self-reported symptoms and more genes detected, with at most small effects of sex, ethnicity, and age. Single-gene positives almost invariably had Ct > 30, but Cts varied widely in triple-gene positives, including without symptoms. Population-level Cts changed over time, with declining Ct preceding increasing SARS-CoV-2 positivity. Of 6189 participants with IgG S-antibody tests post-first RT-PCR-positive, 4808 (78%) were ever antibody-positive; Cts were significantly higher in those remaining antibody negative.

Conclusions:

Marked variation in community SARS-CoV-2 Ct values suggests that they could be a useful epidemiological early-warning indicator.

Funding:

Department of Health and Social Care, National Institutes of Health Research, Huo Family Foundation, Medical Research Council UK; Wellcome Trust.

Article activity feed

  1. Version published to 10.7554/elife.64683 on eLife
  2. Version published to 10.1101/2020.10.25.20219048v2 on medRxiv
  3. eLife

    Author Response:

    Reviewer #1 (Public Review):

    This paper presents the exciting statement that increasing viral loads within a community can be used as an epidemiological early-warning indicator preceeding increased positivity. It would be interesting to support this claim to present both Ct and positivity on the same graph to demonstrate that indeed, declining Ct can be used as an early marker of a COVID-19 epidemic wave. Percentage of positive test data should not only include the ones obtained in the present study but should be compared with "national data" as the present study design includes a bias in patients selection that might not reflect the "true" situation at the time. Only with this comparison, we could claim that the present study design could predict COVID-19 epidemic waves. A correlation of Ct with clinical evidence to rank the confidence of positive results is also included and further support the high specificity of the RT-PCR for detecting SARS-CoV-2 (99.995%).

    In a serological investigation, it was observed that some of these RT-PCR-positive cases do not appear to seroconvert and that possible re-infections might occures despite the presence of anti-spike antibodies. Although, reported on few individuals and therefore to be taken with extreme caution, this add some piece of information to the current unknown of the serological response of COVID-19 patient and would be of uttermost importance in the context of the current vaccination campaign.

    We do not agree that this study is biased in terms of patient selection – it invites randomly selected households to join the survey and is in fact the major source of unbiased surveillance data in the 4 nations of the United Kingdom.

  4. eLife

    Reviewer #1 (Public Review):

    This paper presents the exciting statement that increasing viral loads within a community can be used as an epidemiological early-warning indicator preceding increased positivity. It would be interesting to support this claim to present both Ct and positivity on the same graph to demonstrate that indeed, declining Ct can be used as an early marker of a COVID-19 epidemic wave. Percentage of positive test data should not only include the ones obtained in the present study but should be compared with "national data" as the present study design includes a bias in patients selection that might not reflect the "true" situation at the time. Only with this comparison, we could claim that the present study design could predict COVID-19 epidemic waves. A correlation of Ct with clinical evidence to rank the confidence of positive results is also included and further support the high specificity of the RT-PCR for detecting SARS-CoV-2 (99.995%).

    In a serological investigation, it was observed that some of these RT-PCR-positive cases do not appear to seroconvert and that possible re-infections might occur despite the presence of anti-spike antibodies. Although, reported on few individuals and therefore to be taken with extreme caution, this add some piece of information to the current unknown of the serological response of COVID-19 patient and would be of uttermost importance in the context of the current vaccination campaign.

  5. eLife

    Evaluation Summary:

    The authors present a systematic and complete study of Ct (cycle threshold) values in RT-PCR tests and gene-specific positivity for the UK ONS infection survey. There are very few datasets like this for any viral pathogen, regardless of pandemics. The patterns are fascinating and thought-provoking.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

  6. ScreenIT

    SciScore for 10.1101/2020.10.25.20219048: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: If anyone aged 2 years or older currently resident in an invited household agreed verbally to participate, a study worker visited the household to take written informed consent, which was obtained from parents/carers for those 2-15 years; those aged 10-15 years provided written assent.
    IRB: The study received ethical approval from the South Central Berkshire B Research Ethics Committee (20/SC/0195).
    RandomizationThe survey randomly selects private households on a continuous basis from address lists and from previous surveys to provide a representative UK sample.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    However, this is also a limitation, since we were not able to comprehensively characterise individual positives. We may have underestimated the initial prevalence of symptoms due to originally asking about current symptoms, although this was predominantly at the earliest weekly visits (so only very transient symptoms between visits would have been missed). Similar rates of symptom reporting in the first and last third of the study suggests that this question was likely generously interpreted in any case. We made no attempt to collect additional information on symptoms after positives were identified to minimise recall bias. This may partly explain why we observed higher rates of positive tests without reported symptoms than recent reviews[4, 5]; however, many studies in these reviews tested close contacts of index cases identified through symptoms and therefore might plausibly have higher viral loads. Ultimately the importance of asymptomatic and low virus level infections depends on their transmissibility and their prevalence; regardless of limitations in symptom ascertainment, infection without recognition has the potential for onward transmission and unascertained infections are likely critical for avoiding resurgence after lifting lockdown[25]. Our findings support the use of Ct values and genes detected more broadly in public testing programmes, predominantly testing symptomatic individuals and case contacts, as an “early warning” system for shifts in potential infectiou...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    ISRCTN21086382NANA

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  7. Version published to 10.1101/2020.10.25.20219048v1 on medRxiv