Detection of SARS-CoV-2 infection in the general population by three prevailing rapid antigen tests: cross-sectional diagnostic accuracy study

  1. Roderick P. Venekamp
  2. Irene K. Veldhuijzen
  3. Karel G. M. Moons
  4. Wouter van den Bijllaardt
  5. Suzan D. Pas
  6. Esther B. Lodder
  7. Richard Molenkamp
  8. Zsofi Igloi
  9. Constantijn Wijers
  10. Claudy Oliveira dos Santos
  11. Sylvia B. Debast
  12. Marjan J. Bruins
  13. Khaled Polad
  14. Carla R. S. Nagel-Imming
  15. Wanda G. H. Han
  16. Janneke H. H. M. van de Wijgert
  17. Susan van den Hof
  18. Ewoud Schuit

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Background

Rapid antigen diagnostic tests (Ag-RDTs) are the most widely used point-of-care tests for detecting SARS-CoV-2 infection. Since the accuracy may have altered by changes in SARS-CoV-2 epidemiology, indications for testing, sampling and testing procedures, and roll-out of COVID-19 vaccination, we evaluated the performance of three prevailing SARS-CoV-2 Ag-RDTs.

Methods

In this cross-sectional study, we consecutively enrolled individuals aged >16 years presenting for SARS-CoV-2 testing at three Dutch public health service COVID-19 test sites. In the first phase, participants underwent either BD-Veritor System (Becton Dickinson ), PanBio (Abbott ), or SD-Biosensor (Roche Diagnostics ) testing with routine sampling procedures. In a subsequent phase, participants underwent SD-Biosensor testing with a less invasive sampling method (combined oropharyngeal-nasal [OP-N] swab). Diagnostic accuracies were assessed against molecular testing.

Results

Six thousand nine hundred fifty-five of 7005 participants (99%) with results from both an Ag-RDT and a molecular reference test were analysed. SARS-CoV-2 prevalence and overall sensitivities were 13% (188/1441) and 69% (129/188, 95% CI 62–75) for BD-Veritor, 8% (173/2056) and 69% (119/173, 61–76) for PanBio, and 12% (215/1769) and 74% (160/215, 68–80) for SD-Biosensor with routine sampling and 10% (164/1689) and 75% (123/164, 68–81) for SD-Biosensor with OP-N sampling. In those symptomatic or asymptomatic at sampling, sensitivities were 72–83% and 54–56%, respectively. Above a viral load cut-off (≥5.2 log 10 SARS-CoV-2 E-gene copies/mL), sensitivities were 86% (125/146, 79–91) for BD-Veritor, 89% (108/121, 82–94) for PanBio, and 88% (160/182, 82–92) for SD-Biosensor with routine sampling and 84% (118/141, 77–89) with OP-N sampling. Specificities were >99% for all tests in most analyses. Sixty-one per cent of false-negative Ag-RDT participants returned for testing within 14 days (median: 3 days, interquartile range 3) of whom 90% tested positive.

Conclusions

Overall sensitivities of three SARS-CoV-2 Ag-RDTs were 69–75%, increasing to ≥86% above a viral load cut-off. The decreased sensitivity among asymptomatic participants and high positivity rate during follow-up in false-negative Ag-RDT participants emphasise the need for education of the public about the importance of re-testing after an initial negative Ag-RDT should symptoms develop. For SD-Biosensor, the diagnostic accuracy with OP-N and deep nasopharyngeal sampling was similar; adopting the more convenient sampling method might reduce the threshold for professional testing.

Article activity feed

  1. Version published to 10.1186/s12916-022-02300-9
  2. ScreenIT

    SciScore for 10.1101/2021.11.19.21266579: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Individuals were considered eligible if they were aged 16 years or older, and willing and able to sign an informed consent in Dutch.
    Sex as a biological variableSecondary outcomes were diagnostic accuracies using a viral load cut-off as a proxy of infectiousness (≥5.2 log10 SARS-CoV-2 E-gene copies/mL), which was the viral load cut-off above which 95% of people with a positive molecular test had a positive virus culture in a recent study by our group6, and diagnostic accuracies stratified by presence of symptoms at time of sampling (yes or no), COVID-19 vaccination status (vaccinated with at least one dose yes or no), having had a prior SARS-CoV-2 infection (yes or no), sex (female or male), age (≥16 to ≤40 or >40 to ≤65 or >65), and testing indication (symptoms and/or close contact without symptoms).
    Randomizationnot detected.
    BlindingAll staff assessing test results were blinded to the results of the other test.
    Power AnalysisSample size calculation: Previous diagnostic accuracy studies of Ag-RDTs in people with COVID-19-like symptoms found sensitivities of around 80-85%.3-5,11,12 We based our sample size calculation on an expected sensitivity of 80% for each Ag-RDT, with a margin of error of 7%, type I error of 5% and power of 90%.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The study is reported according to the STARD 2015 guidelines: an updated list of essential items for reporting diagnostic accuracy studies.
    STARD
    suggested: None
    In discordant cases (Ag-RDT negative and RT-PCR positive cases) whole genome sequencing (WGS) of the primary clinical sample was performed when the viral load was above the infectiousness cut-off (supplementary material 2).
    WGS
    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:
    Strengths and limitations of this study: Strengths include the protocolised nature of the study, the large sample size covering multiple test sites nationwide, the high data completeness, collection of samples for the index and reference tests at the same time, the implementation of index and reference tests by trained staff who were blinded to the result of the other test, and the availability of follow up information for participants who received negative test results. Our study also has some limitations. First, the reference standards that we used were molecular tests, but platforms and test kits used differed among the three centralised laboratories. However, the diagnostic accuracies of all molecular tests used are similarly high13,14, and we therefore believe that this has not influenced our findings significantly. In addition, Ct values determined by the different platforms were comparable (supplementary material 2). Second, we were unable to meet the predefined sample size in the PanBio/OP-N sampling group. These results are therefore not sufficiently robust and should be interpreted with great caution. Third, while the Delta variant is the dominant SARS-CoV-2 variant in the Netherlands at time of writing, its prevalence was only around 8.6% during the last week of inclusions. However, we checked whether false-negative Ag-RDT results could be linked to specific virus lineages by WGS and we did not find a signal confirming this hypothesis. Fourth, we relied on infectio...

    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.

    Results from scite Reference Check: We found no unreliable references.

    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.

  3. Version published to 10.1101/2021.11.19.21266579v1 on medRxiv