Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infectivity by Viral Load, S Gene Variants and Demographic Factors, and the Utility of Lateral Flow Devices to Prevent Transmission

  1. Lennard Y W Lee
  2. Stefan Rozmanowski
  3. Matthew Pang
  4. Andre Charlett
  5. Charlotte Anderson
  6. Gareth J Hughes
  7. Matthew Barnard
  8. Leon Peto
  9. Richard Vipond
  10. Alex Sienkiewicz
  11. Susan Hopkins
  12. John Bell
  13. Derrick W Crook
  14. Nick Gent
  15. A Sarah Walker
  16. Tim E A Peto
  17. David W Eyre

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Abstract

Background

How severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectivity varies with viral load is incompletely understood. Whether rapid point-of-care antigen lateral flow devices (LFDs) detect most potential transmission sources despite imperfect clinical sensitivity is unknown.

Methods

We combined SARS-CoV-2 testing and contact tracing data from England between 1 September 2020 and 28 February 2021. We used multivariable logistic regression to investigate relationships between polymerase chain reaction (PCR)-confirmed infection in contacts of community-diagnosed cases and index case viral load, S gene target failure (proxy for B.1.1.7 infection), demographics, SARS-CoV-2 incidence, social deprivation, and contact event type. We used LFD performance to simulate the proportion of cases with a PCR-positive contact expected to be detected using 1 of 4 LFDs.

Results

In total, 231 498/2 474 066 (9%) contacts of 1 064 004 index cases tested PCR-positive. PCR-positive results in contacts independently increased with higher case viral loads (lower cycle threshold [Ct] values), for example, 11.7% (95% confidence interval [CI] 11.5–12.0%) at Ct = 15 and 4.5% (95% CI 4.4–4.6%) at Ct = 30. B.1.1.7 infection increased PCR-positive results by ~50%, (eg, 1.55-fold, 95% CI 1.49–1.61, at Ct = 20). PCR-positive results were most common in household contacts (at Ct = 20.1, 8.7% [95% CI 8.6–8.9%]), followed by household visitors (7.1% [95% CI 6.8–7.3%]), contacts at events/activities (5.2% [95% CI 4.9–5.4%]), work/education (4.6% [95% CI 4.4–4.8%]), and least common after outdoor contact (2.9% [95% CI 2.3–3.8%]). Contacts of children were the least likely to test positive, particularly following contact outdoors or at work/education. The most and least sensitive LFDs would detect 89.5% (95% CI 89.4–89.6%) and 83.0% (95% CI 82.8–83.1%) of cases with PCR-positive contacts, respectively.

Conclusions

SARS-CoV-2 infectivity varies by case viral load, contact event type, and age. Those with high viral loads are the most infectious. B.1.1.7 increased transmission by ~50%. The best performing LFDs detect most infectious cases.

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  1. Version published to 10.1093/cid/ciab421
  2. ScreenIT

    SciScore for 10.1101/2021.03.31.21254687: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Ethics: The study was conducted as part of national COVID-19 surveillance under the provisions of Section 251 of the NHS Act 2006 and therefore did not require individual patient consent.
    IRB: The protocol for this work was reviewed by the PHE Research Ethics and Governance Group, which is the PHE Research Ethics Committee, and was found to be fully compliant with all regulatory requirements.
    RandomizationSimulations of the number of cases identified by antigen LFDs: We used our findings to estimate the proportion of potential transmission events where the source case would have been detected using an antigen LFD, using existing data on the sensitivity of four LFDs: Innova, Deep Blue, Orient gene and Abbott.18 For each source case we simulated a positive or negative LFD result by randomly drawing from the probability of a LFD being positive by the source case’s Ct value (see Supplement, Figure S1).
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Samples were processed using the same RNA extraction and Thermo Fisher TaqPath PCR platform in each laboratory (targeting S and N genes, and ORF1ab; details in Supplement).
    Thermo Fisher TaqPath
    suggested: None

    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:
    Our study has important limitations. Firstly, ascertaining infection in contacts depends on the contact being reported by the case and the contact being tested. In the UK, PCR testing is only recommended for those with symptoms and therefore we do not ascertain most asymptomatic infections. Whilst Ct values are generally slightly lower in those without symptoms,22 they may nevertheless contribute substantially to transmission.23 Additionally, access to testing depends on social and demographic factors, e.g. the relationships between PCR-positive results in contacts and ethnicity varied if we conditioned on contact attendance for a PCR test (Table 2 vs. Table S2). Secondly, our classification of contact events is relatively simple, e.g., we do not have any direct measures of human behaviour, such as proximity or duration of contact. We also do not account for the dynamic nature of viral loads over time,24 relying on a single measurement at varying times post infection. Despite this, the time from symptom onset to testing in the cases was relatively consistent, median (IQR) 2 (1-3) days, such that measured Ct values plausibly represent similar stages of the illness in cases. We use only a single assay to determine Ct values, but have calibrated this to allow comparison with other platforms. Finally, it was not possible to account for unobserved third-party transmission, although we designed our study population to minimise this risk. This likely means that some contact events i...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    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

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  3. Version published to 10.1101/2021.03.31.21254687 on medRxiv