Performance of Various Lateral Flow SARS-CoV-2 Antigen Self Testing Methods in Healthcare Workers: a Multicenter Study

medRxiv

Abstract

Abstract Introduction Rapid antigen detection tests (RDT) are suitable for large-scale testing for SARS-CoV-2 among the population and recent studies have shown that self-testing with RDT in the general population is feasible and yields acceptable sensitivities with high specificity. We aimed to determine the accuracy of two different RDT’s, with two different sample collection methods for one of the RDT’s among healthcare workers (HCW). Secondary objectives were to determine the accuracy of RDT using a viral load cut-off as proxy of infectiousness and to identify predictors for a false negative RDT. Methods Centers that participated were secondary care hospitals, academic teaching hospitals, and long-term care facilities. All HCW that met inclusion criteria were asked to perform a RDT self-test next to a regular SARS-CoV-2 nucleic acid amplification test (NAAT). Three study groups were created. Study group 1; Veritor(tm) System, Becton Dickinson, Franklin Lakes, USA (BD-RDT) with combined oropharyngeal - mid-turbinate nasal sampling, group 2; BD-RDT with mid-turbinate nasal sampling only and group 3; SD Biosensor SARS-CoV-2 Rapid Antigen Test, Roche, Basel, Switzerland (Roche-RDT) with combined oropharyngeal - mid-turbinate nasal sampling. RDT accuracy was calculated using NAAT as reference standard. For samples processed in the cobas ® 6800/8800 platform (Roche Diagnostics, Basel, Switzerland), established cycle threshold values (Ct-values) could be converted into viral loads. A viral load cut-off of ≥5.2 log10 SARS-CoV-2 E gene copies/ml was used as proxy of infectiousness. Logistic regression analysis was performed to identify predictors for a false negative RDT. Results In total, 7,196 HCW were included. Calculated sensitivities were 61.5% (95%CI 56.6%-66.3%), 50.3% (95%CI 42.8%-57.7%) and 74.2% (95%CI 66.4%-80.9%) for study groups 1, 2 and 3, respectively. After application of a viral load cut-off as a proxy for infectiousness for samples processed in the cobas ® 6800/8800 platform sensitivities increased to 82.2% (95%CI 76.6-86.9%), 61.9% (95%CI 48.8%-73.9%) and 90.2% (95%CI 76.9%-97.3%) for group 1, group 2 and group 3, respectively. Multivariable regression analysis showed that use of Roche-RDT (p <0.01), combined oropharyngeal - mid-turbinate nasal sampling (p <0.05) and the presence of COVID-19 like symptoms at the time of testing (p <0.01) significantly reduced the likeliness of a false-negative RDT result. Conclusion SARS-CoV-2 RDT has proven able to identify infectious individuals, especially when upper respiratory specimen is collected through combined oropharyngeal - mid-turbinate sampling. Reliability of self-testing with RDT among HCW seems to depend on the type of RDT, the sampling method and the presence of COVID-19 like symptoms at the time of testing.

Authors 14

1. Vivian F. Zwart corresponding
   Affiliation as printed

   Microvida, Laboratory of Medical Microbiology and Immunology, location Amphia, Breda, The Netherlands

   Microvida, Laboratory of Medical Microbiology and Immunology, location Elisabeth-TweeSteden, Tilburg, The Netherlands

2. Nathalie Van der Moeren
   Affiliation as printed

   Microvida, Laboratory of Medical Microbiology and Immunology, location Amphia, Breda, The Netherlands

   Microvida, Laboratory of Medical Microbiology and Immunology, location Elisabeth-TweeSteden, Tilburg, The Netherlands

3. Joep Stohr
   Affiliation as printed

   Microvida, Laboratory of Medical Microbiology and Immunology, location Amphia, Breda, The Netherlands

   Microvida, Laboratory of Medical Microbiology and Immunology, location Elisabeth-TweeSteden, Tilburg, The Netherlands

4. Mariet C.W. Feltkamp Aachen Department of Medical Microbiology

   Leiden University Medical Center

   Affiliation as printed

   Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands

5. Robbert Gerard Bentvelsen Aachen Department of Medical Microbiology

   Leiden University Medical Center · ZorgSaam

   Affiliation as printed

   Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands

   Microvida, Laboratory of Medical Microbiology and Immunology, location Amphia, Breda, The Netherlands

   Microvida, Laboratory of Medical Microbiology and Immunology, location ZorgSaam, Terneuzen, The Netherlands

6. Bram M. W. Diederen

   Bravis Ziekenhuis

   Affiliation as printed

   Microvida, Laboratory of Medical Microbiology and Immunology, location Bravis, Roosendaal, The Netherlands

7. A.C. de Laat
   Affiliation as printed

   Mijzo, Geertruidenberg, The Netherlands

8. Ellen M. Mascini

   Rijnstate Hospital

   Affiliation as printed

   Laboratory for Medical Microbiology and Immunology, Rijnstate, Arnhem, The Netherlands

9. I. Schilders
   Affiliation as printed

   Stichting Prisma, Biezenmortel, The Netherlands

10. H.T.M. Vlassak

    GGZ Oost Brabant

    Affiliation as printed

    GGZ Oost-Brabant, Mental Health Hospital, location Boekel, The Netherlands

11. Heiman F. L. Wertheim

    Radboud University Medical Center

    Affiliation as printed

    Department of Medical Microbiology, Radboud University Medical Center, Nijmegen, The Netherlands

12. Jean‐Luc Murk
    Affiliation as printed

    Microvida, Laboratory of Medical Microbiology and Immunology, location Amphia, Breda, The Netherlands

    Microvida, Laboratory of Medical Microbiology and Immunology, location Elisabeth-TweeSteden, Tilburg, The Netherlands

13. Jan A. J. W. Kluytmans

    Utrecht University · University Medical Center Utrecht

    Affiliation as printed

    Department of medical Microbiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands

14. Wouter van den Bijllaardt

    Amphia Ziekenhuis

    Affiliation as printed

    Department of infection control, Amphia, Breda, The Netherlands

    Microvida, Laboratory of Medical Microbiology and Immunology, location Amphia, Breda, The Netherlands