Journal of Clinical Virology

A nationwide analytical and clinical evaluation of 46 rapid antigen tests for SARS-CoV-2 compared to RT-qPCR

--Manuscript Draft--

Manuscript Number: JCV-D-22-00099R1

Article Type: Full length article

Keywords: rapid antigen tests; SARS-CoV-2; Analytical sensitivity and specificity; Clinicalsensitivity and specificity; point of care tests; reverse transcriptation quantitativepolymerase chain reaction

Corresponding Author: Uffe Schneider, Ph.D., M.D.Hvidovre HospitalHvidovre, DENMARK

First Author: Uffe Schneider, Ph.D., M.D.

Order of Authors: Uffe Schneider, Ph.D., M.D.

Maria Wendelboe Forsberg, MLS

Thomas Daell Leineweber, MD

Christel Barker Jensen, PhD

Khaled Ghathian, MLS,MEd

Charlotte Nielsen Agergaard, MD

Kasper Kjersgaard Mortensen, MD

Arieh Cohen, PhD

Charlotte Sværke Jørgensen, PhD

Helene Larsen, PhD

Matilde Bøgelund Hansen, MSc

Ulla Saleme, BMed

Anders Koch, PhD

Nikolai Søren Kirkby, PhD

Thomas Kallemose, MSc

Marie Louise Schaadt, MD

Frederikke Holm Jensen, MD

Rikke Lind Jørgensen, MSc

Chih Man German Ma, MLS

Nina Steenhard, PhD

Jenny Dahl Knudsen, DMSc

Jan Gorm Lisby, PhD

Abstract: Background

The SARS-CoV-2 pandemic has resulted in massive testing by Rapid Antigen Tests(RAT) without solid independent data regarding clinical performance being available.Thus, decision on purchase of a specific RAT may rely on manufacturer-provided dataand limited peer-reviewed data.

Methods

This study consists of two parts. In the retrospective analytical part, 33 RAT and a

Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation

Strand Invasion Based Amplification (SIBA)-rt-PCR test from 26 manufacturers werecompared to RT-qPCR on 100 negative and 204 positive deep oropharyngeal cavitysamples divided into four groups based on RT-qPCR Cq levels. In the prospectiveclinical part, 200 individuals found SARS-CoV-2 positive and 200 individuals foundSARS-CoV-2 negative by routine RT-qPCR testing were tested within 72 hours with 46included RAT from 28 manufacturers applying RT-qPCR as the reference method.

Results

The overall analytical sensitivity differed significantly between the 34 included RAT;from 2.5% (95% CI 0.5-4.8) to 67% (95% CI 60-73). All RAT presented analyticalspecificities between 93-100%. Likewise, the overall clinical sensitivity variedsignificantly between the 46 included RAT; from 2.5% (95% CI 0.5-4.8) to 94 % (95%CI 91-97). All RAT presented clinical specificities between 97-100%.

Conclusion

The study presents analytical as well as clinical performance data for 46 commerciallyavailable RAT compared to the same RT-qPCR test. The study enables identificationof individual RAT that has significantly higher sensitivity than other included RAT andmay aid decision makers in selecting between the included RAT.

Funding

The study was funded by a participant fee for each test and the Danish Regions.

Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation

Conflict of interest

Lars Østergaard has within 36 months received speaker fees from Sanofi-Pasteur and Pfizer. None of the

other authors have any personal conflict of interests to report. The project received a participation fee

from each of the participating companies to cover the cost of the project.

Conflict of Interest

A nationwide analytical and clinical evaluation of 46 rapid antigen tests for SARS-CoV-2 compared to RT-

qPCR

Uffe Vest Schneider, PhD1; Maria Wendelboe Forsberg, MLS1; Thomas Daell Leineweber, MD1; Christel

Barker Jensen PhD1; Khaled Ghathian MEd1; Charlotte Nielsen Agergaard, MD2; Kasper Kjersgaard

Mortensen, MD3; Arieh Cohen, PhD4; Charlotte Sværke Jørgensen, PhD5; Helene Larsen, PhD6; Matilde

Bøgelund Hansen, MSc7; Ulla Saleme, BMed8; Anders Koch, PhD9; Nikolai Søren Kirkby, PhD10; The National

Danish RAT testing group11; Thomas Kallemose, MSc12; Marie Louise Schaadt, MD1; Frederikke Holm Jensen,

MD1; Rikke Lind Jørgensen MSc1; Chih Man German Ma, MLS1; Nina Steenhard, PhD4; Jenny Dahl Knudsen,

DMSc10; Jan Gorm Lisby, PhD 1

1 Copenhagen University Hospital Hvidovre, Department of Clinical Microbiology, Kettegaard Alle 30, 2650

Hvidovre, Denmark

2 Odense University Hospital, Department of Clinical Microbiology, J. B. Winsløws Vej 21, 2., 5000 Odense C,

Denmark

3 Aarhus University Hospital, Department of Clinical Microbiology, Palle Juul-Jensens Boulevard 99, Skejby,

8200 Aarhus N., Denmark

4 Danish National Test Center, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark

5 Statens Serum Institut, Department of Virus & Microbiological Special Diagnostics, Artillerivej 5, 2300

Copenhagen, Denmark

6 Technical University of Denmark - DTU, Centre for Diagnostics Department of Health Technology, Henrik

Dams Allé, 2800 Kgs Lyngby, Denmark

7 Copenhagen University Hospital Herlev and Gentofte, Department of Clinical Microbiology, Borgmester Ib

Juuls Vej 52, 2730 Herlev, Denmark

8 Copenhagen University Hospital Bispebjerg and Frederiksberg, Department of Clinical Biochemistry,

Nielsine Nielsens Vej 4B, 2400 Copenhagen, Denmark

9 Rigshospitalet University Hospital, Department of Infectious Diseases, Blegdamsvej 9, 2100 Copenhagen,

Denmark

10 Rigshospitalet, Department of Clinical Microbiology, Henrik Harpestrengsvej 4A, 2100 Copenhagen,

Denmark

11 The Danish National rapid antigen testing group

12 Copenhagen University Hospital Hvidovre, Department of Clinical Research, Kettegaard Alle 30, 2650

Hvidovre, Denmark

Title Page (including author details, affiliations and word count)

Corresponding author

Uffe Vest Schneider,

Copenhagen University Hospital Hvidovre, Department of Clinical Microbiology, Kettegaard Alle 30, 2650

Hvidovre, Denmark

Email: Uffe.vest.schneider@regionh.dk

Phone: +45 38622429

The National Danish RAT testing group First name Surname

John Eugenio Coia

Svend Ellermann-Eriksen

Lennart Friis-Hansen

David Fuglsang-Damgaard

Jens Otto Jarløv

Ulrich Stab Jensen

Sanne Jespersen

Ea Sofie Marmolin

Lene Nielsen

Xiaohui Chen Nielsen

Anel Ramic

Lars Jørgen Østergaard

The clinical sensitivity among 46 rapid antigen tests for SARS-CoV-2 varied from 0.03 [95% CI 0.01-0.05] to

0.94 [0.91-0.97]

29 rapid antigen tests performed significantly worse than the 17 best performing rapid antigen tests in the

study

The study demonstrates that analytical sensitivity cannot be directly translated to clinical sensitivity for

individual SARS-CoV-2 rapid antigen tests

Highlights (for review)

1

Abstract 1

Background 2

The SARS-CoV-2 pandemic has resulted in massive testing by Rapid Antigen Tests (RAT) without solid 3

independent data regarding clinical performance being available. Thus, decision on purchase of a specific 4

RAT may rely on manufacturer-provided data and limited peer-reviewed data. 5

Methods 6

This study consists of two parts. In the retrospective analytical part, 33 RAT and a Strand Invasion Based 7

Amplification (SIBA)-rt-PCR test from 26 manufacturers were compared to RT-qPCR on 100 negative and 8

204 positive deep oropharyngeal cavity samples divided into four groups based on RT-qPCR Cq levels. In the 9

prospective clinical part, 200 individuals found SARS-CoV-2 positive and 200 individuals found SARS-CoV-2 10

negative by routine RT-qPCR testing were tested within 72 hours with 46 included RAT from 28 11

manufacturers applying RT-qPCR as the reference method. 12

Results 13

The overall analytical sensitivity differed significantly between the 34 included RAT; from 2.5% (95% CI 0.5-14

4.8) to 67% (95% CI 60-73). All RAT presented analytical specificities between 93-100%. Likewise, the 15

overall clinical sensitivity varied significantly between the 46 included RAT; from 2.5% (95% CI 0.5-4.8) to 94 16

% (95% CI 91-97). All RAT presented clinical specificities between 97-100%. 17

Conclusion 18

The study presents analytical as well as clinical performance data for 46 commercially available RAT 19

compared to the same RT-qPCR test. The study enables identification of individual RAT that has significantly 20

higher sensitivity than other included RAT and may aid decision makers in selecting between the included 21

RAT. 22

Funding 23

The study was funded by a participant fee for each test and the Danish Regions. 24

Introduction 25

During the current SARS-CoV-2 pandemic, massive testing has been applied with the aim to contain the 26

spread of the virus. The test strategy was emphasized by the WHO in March, 2020 as the backbone of the 27

global pandemic response together with isolation and contact tracing that combined with social distancing 28

and hand hygiene would allow “to extinguish” the pandemic [1]. 29

Revised Manuscript (text UNmarked) Click here to view linked References

2

The unprecedented demand for testing has led to a shortage of reagents and manufactured tests for 30

reverse transcription quantitative polymerase chain reaction (RT-qPCR) and other nucleic acid amplification 31

technology (NAAT) methods including point of care testing (PoCT). Thus, lateral flow based rapid antigen 32

tests (RAT) have been deployed extensively due to delivery of results within minutes, availability, low cost 33

and the ease of use that allow non-healthcare trained individuals to perform the test outside of healthcare 34

facilities [2,3]. 35

Several approaches to evaluate real-life performance of RAT has been applied, including studies on cultured 36

virus, retrospective studies evaluating analytical performance data and clinical evaluations [4–13]. 37

Viral culture studies have shown that limit of detection (LOD) of RAT differs significantly and varies 38

depending on spike variants of SARS-CoV-2 [4,14]. SARS-CoV-2 variants contain several mutations in the 39

nucleocapsid gene together with mutations in the spike gene, which may account for the difference in LOD 40

[15]. 41

Clinical studies have shown that sensitivity of a single RAT may vary at least 20 percentage point between 42

non-symptomatic and symptomatic individuals [9,16–18]. As most clinical studies only include a single or 43

few different RAT and as the tested population varies between different clinical studies regarding SARS-44

CoV-2 prevalence, proportion of symptomatic versus non-symptomatic individuals, vaccination status and 45

demographic profile, comparing performance data between different studies is difficult [9–11,19,20]. Due 46

to the absence of clinical studies that allow for comparison of the different performances of commercially 47

available RAT and the huge amount of financial resources spent on RAT, the Danish Regions initiated a 48

nationwide clinical study comparing different RAT. This study combines a retrospective analytical sensitivity 49

and specificity study on 100 negative and 204 positive frozen samples with a prospective clinical study on 50

sensitivity and specificity, in which approximately 200 SARS-CoV-2 positive individuals and 200 SARS-CoV-2 51

negative individuals were tested by routine RT-qPCR and a number of RAT within 72 hours of the initial RT-52

qPCR test. 53

Methods 54

For detailed description of protocol and methods, please refer to Supplementary data and [21]. 55

Study design 56

A total of 46 tests, 44 RAT and two SIBA-rt-PCR from 28 manufacturers, were included in the study. 57

3

Participants 58

Individuals, who tested positive for SARS-CoV-2 by routine RT-qPCR performed by a public test provider 59

were included in the study. 60

Retrospective analytical RAT testing 61

UTM samples from SARS-CoV-2 RT-qPCR positive individuals participating in the prospective arm of the 62

study were collected by out-patient testing teams. All samples were collected as deep oropharyngeal swabs 63

and immediately stored at -80 °C until further processing. In total, 50 samples with Cq <25; 54 samples with 64

Cq between 25 and 30; 50 samples with Cq between 30 and 35 and 50 samples with Cq between 35 and 40 65

were prepared. One hundred SARS-CoV-2 RT-qPCR negative samples were prepared by pooling ten routine 66

UTM samples that had tested negative for SARS-CoV-2 for each negative sample (Figure 1A). 67

Prospective clinical RAT testing 68

From each included individual, deep oropharyngeal swabs, anterior nasal cavity swabs and saliva were 69

collected for RAT testing together with a deep oropharyngeal swab for RT-qPCR testing. All tests were 70

conducted according to the IFU or according to additional instruction from the manufacturer using the 71

utensils provided for testing by the manufacturer. Samples collected from other anatomical sites than CE-72

marked were collected and handled as instructed by each manufacturer. 73

Prospective RT-qPCR 74

Deep oropharyngeal swabs for RT-qPCR were collected in a NEST disposable sampler inactivation transport 75

medium with an oropharyngeal specimen collection swab (Wuxi NEST Biotechnology Co., Ltd, Wuxi City, 76

China) and sent to RT-qPCR testing. 77

Analysis 78

Dual-target RT-qPCR was used as gold standard. In the retrospective part of the study, samples were 79

grouped into four Cq ranges based on the highest Cq level of the two E- and N-targets. In the prospective 80

part of the study, samples were grouped into three Cq ranges based on the average Cq level between the 81

two N-targets. 82

Sensitivity and specificity were calculated for each individual RAT in relation to RT-qPCR. All p-values less 83

than 0.05 were considered statistically significant. 84

Role of the funding source 85

The participating companies had no influence on study design, sample collection, analysis, interpretation, 86

drafting of manuscript, or decision on publishing. 87

4

Results 88

Participants and SARS-CoV-2 variants 89

A total of 3,797 individuals were included in the prospective part of the study between January 18th, 2021 90

and September 9th, 2021 to allow each RAT to be tested on 200 SARS-CoV-2 positive and 200 SARS-CoV-2 91

negative individuals. 2,045 individuals that had just tested positive for SARS-CoV-2 were included in the 92

study within 72 hours and 1,752 SARS-CoV-2 expected RT-qPCR negative individuals were included after 93

screening at a regional test center. Among the newly positive individuals for SARS-CoV-2, twelve individuals 94

were excluded due to missing sample for RT-qPCR (n = 3) or a negative RT-qPCR test including the human 95

control target (n = 9). Among the remaining 2,033 individuals, 140 (6.9%) were negative by the concomitant 96

RT-qPCR at the time of RAT testing (Figure 1B), resulting in inclusion of 1,893 positive individuals among the 97

previous SARS-CoV-2 positive individuals. In the screening group, forty-three individuals were excluded, 98

eight samples were missing for RT-qPCR and thirty-five samples were negative for all targets including the 99

human sampling control. Thus, a total of 1,709 SARS-CoV-2 negative or positive individuals by RT-qPCR 100

were included in the screening group. The SARS-CoV-2 prevalence in the screening group was 0.64%, as 11 101

out of 1,709 individuals were positive for SARS-CoV-2 by RT-qPCR (Figure 1B). Participating individuals were 102

predominantly between 18 and 70 years of age with few individuals above 70 years of age. Study 103

participants were mainly unvaccinated at the time of inclusion. 104

The alpha variant (B.1.1.7) was the predominating variant among SARS-CoV-2 positive individuals included 105

in the study and accounted for 90.8% (1,729 of 1,904) of all cases (Supplementary data). 106

Analytical sensitivity and specificity of RAT 107

The overall analytical sensitivity differed significantly between the 34 included tests from 26 108

manufacturers. The SIBA-rt-PCR based assay had the highest overall sensitivity of 67% (95% CI 60-73), but 109

also the lowest specificity of 93% (95% CI 88-98%). The RAT varied from 2.5% (95% CI 0.5-4.8) for the Lituo 110

saliva RAT to 42% (95% CI 35-49) for the Acro RAT. All RAT had a specificity of 100% (Figure 2). The overall 111

mean sensitivity for the tests was 26% (95% CI 21-32), which reflects that RAT detected almost none of the 112

samples with Cq >35 by RT-qPCR (n = 50). For RT-qPCR samples with Cq 30-35 (n = 50), the mean sensitivity 113

was 2.5% (95% CI 1.5-3.8) but increased at Cq 25-30 (n = 54) with a mean sensitivity of 32% (95% CI 21-42) 114

and a mean sensitivity of 71% (95% CI 61-80, range 6.2-99) for samples with RT-qPCR Cq <25 (n = 50) 115

(Supplementary data). 116

5

Clinical sensitivity and specificity of RAT 117

In the prospective part of the study, the overall clinical sensitivity varied significantly among the 46 118

included tests from 28 manufacturers; from 2.5% (95% CI 0.5-4.8) for the Quidel saliva RAT to 94% (95% CI 119

91-97) for the Acon Flowflex RAT, with a mean overall sensitivity of 69% (95% CI 63-74). Specificity varied 120

among the RAT from 98% (95% CI 95-99) for the Abbott nasal RAT to 100% for 28 RAT, whereas the Qlife 121

SIBA-rt-PCR Egoo system had the lowest specificity of 97% (95% CI 95-99) for anterior nasal cavity swabs 122

(Figure 3). According to CE-mark, the sensitivities for all tests were reported to be 81% (95% CI 69-89) or 123

above and specificities were reported from 97% (95% CI 91-99) and above (Supplementary data). 124

The sensitivity of the Acon Flowflex RAT did not differ significantly from 16 of the other RAT from 14 125

manufacturers, when multiple testing was taken into account. The remaining 29 RAT (including the visual 126

and automated read-out of the BD veritor RAT) had a significantly lower overall sensitivity compared to the 127

Acon Flowflex RAT (Table 1 and Supplementary data). 128

The mean overall sensitivity was 81% (95% CI 74-87) for strong positive samples with Cq <15, which 129

decreased to 70% (95% CI 62-78) for medium positive samples with Cq 15-20 and 44% (95% CI 31-56) mean 130

sensitivity for weak positive samples with Cq >20 (Supplementary data). Three out of the four included self-131

test were among the 17 most sensitive tests in the study, whereas the Wantai saliva/buccal RAT was among 132

the five tests with the lowest sensitivity in the study. The sensitivity of RAT with automated readout was 133

distributed over the full range of sensitivities with the Lumira Dx and Quidel nasal RAT performing among 134

the 17 best tests of the study. 135

Discussion 136

In our study, we used deep oropharyngeal swabs collected for the analytical sensitivity and specificity 137

study. Thirty-four RAT were compared using the same 204 SARS-CoV-2 positive samples and we anticipated 138

that the analytical sensitivity data would correlate with the ranking in clinical sensitivity among the 46 RAT 139

in the prospective part of the study. The prospective study included a higher number of different RAT 140

compared to the retrospective study, as several manufacturers provided identical RAT to be used on 141

several anatomical sampling sites. Interestingly, we saw similarities between analytical sensitivity and 142

clinical sensitivity on SARS-CoV-2 positive individuals, but several tests performed differently between the 143

retrospective and prospective part of study. As an example, the Qlife SIBA-rt-PCR and the Acro RAT 144

presented the highest analytical sensitivity, but both tests performed significantly worse than the Acon 145

Flowflex RAT in the prospective part of the study. Our data shows that anterior nasal cavity RAT in general 146

had higher sensitivity compared to deep oropharyngeal RAT and RAT using saliva for testing performed the 147

6

worst. This may indicate that the Acro RAT using deep oropharyngeal swabs is underperforming in the 148

prospective part of the study as anterior nasal cavity swabs may be a better testing material. Surprisingly, 149

the Qlife SIBA-rt-PCR performed with an unexpected low sensitivity and specificity in the prospective part 150

of the study. This may be due to the small sample volume being used for the test. Furthermore, results 151

were reported by the automated Egoo instrument result-algorithm, which is still under development and 152

previous evaluations of the Qlife SIBA-rt-PCR have been conducted by visual inspection of results instead of 153

the automated result determination [22]. A more general concern regarding the comparison of 154

retrospective and prospective results is that the sampling step, release of material and lysis material from 155

the swab in the lysis buffer are removed from the comparison in retrospective studies, which may lead to 156

underperformance of clinically optimized RAT in analytical studies. 157

The primary strength of this study is that we can identify RAT that perform significantly better than other 158

RAT included in the study, as we report analytical as well as clinical performance data for a large number of 159

commercially available RAT and compare the RAT performance to the same RT-qPCR test on the same 160

samples. 161

This study has several limitations. First, it is important to emphasize that the study was designed to 162

compare performance differences between the included RAT. The data reported in this study cannot be 163

used to predict the sensitivity of a certain RAT in a specific clinical setting. Second, as the out-patient 164

testing teams knew the RT-qPCR result of the included individual prior to sampling and testing by RAT, and 165

as even a weak band should be regarded as a positive test result, the prospective part of the study is biased 166

towards overestimating the sensitivity of each RAT. Third, the current study is likely to overestimate the 167

clinical sensitivity of the included RAT as the study was performed prior to vaccination of the participating 168

age groups. It has previously been shown that vaccination accelerates viral clearance, which may reduce 169

the amount of viral particles released by infected individuals and thereby narrows the time period for a 170

positive RAT [23]. Finally, at the time of the study, the predominant variant of SARS-CoV-2 was the B.1.1.7 171

alpha variant with few cases of the delta variant (B.1.617.2). It has previously been shown that different 172

SARS-CoV-2 variants may influence the analytical sensitivity of different RAT [14], which may translate to 173

differences in clinical sensitivity of RAT if other SARS-CoV-2 variants are predominant [9]. 174

In conclusion, this study compares analytical and clinical sensitivities to RT-qPCR of 46 commercially 175

available RAT and enables identification of individual RAT that has significant higher sensitivity than other 176

included RAT. The study demonstrates significant differences in analytical as well as clinical sensitivities 177

between the included RAT but cannot be used for prediction of the clinical sensitivity in a specific clinical 178

7

setting. The results reported in this study may guide decision makers prior to purchase of RAT for 179

population screening. 180

Acknowledgments 181

All participating companies contributed with a participant’s fee to cover the costs of the study and 182

delivered all necessary RAT and additional materials free of charge. The authors thank bioinformatician 183

Jose Castruita for assisting with the variant analysis of the SARS-CoV-2 positive samples. 184

Authors' contributions 185

UVS, JGL, and JDK conceptuated the study. UVS and JGL were responsible for the funding acquisition. 186

Acquisition of data was conducted by UVS, MWF, TDL, CBJ, KG, CNA, KKM, CSJ, HL, MBJ, US, AK, NSK, The 187

National Danish RAT testing group, MLS, FHJ, RLJ, CMGM, NS, and JGL. Local supervision of research activity 188

was conducted by MWF, CNA, KKM, AC, NS, CSJ, HL, MBH, US, AK, and NSK. Overall project administration 189

was conducted by UVS, MWF, AC, CSJ, JDK, and JGL. Data was curated by CBJ, KG, MWF, CNA, KKM, CSJ, US, 190

NSK, UVS, and JGL. Data was validated by or under supervision of MWF, CBJ, CNA, KKM, CSJ, HL, US, NSK, 191

RLJ, JGL, and UVS. TK and UVS performed the formal analysis of data. 192

UVS and JGL drafted the manuscript with substantial input from JDK. All authors read and commented on 193

the manuscript and all authors approved the final manuscript prior to submission. All authors agree to be 194

held accountable for all aspects of the work. 195

Conflict of interest 196

Lars Østergaard has within 36 months received speaker fees from Sanofi-Pasteur and Pfizer. None of the 197

other authors have any personal conflict of interests to report. The project received a participation fee 198

from each of the participating companies to cover the cost of the project. 199

Ethics committee approval 200

The study was evaluated by the National Committee on Health Research Ethics in the Danish Capital Region 201

to be a method validation study without the need of approval of the committee (decision H-20068579). 202

Access to test results for research was granted by the Capital Region of Denmark – Research and Innovation 203

(R-20083753) and contact to participants without prior consent from the individual was granted by the 204

board of directors at the Hospitals at which the participating DCM are situated. 205

206

8

207

References 208

[1] WHO-Director-General, WHO Director-General’s opening remarks at the media briefing on COVID-209

19 - 16 March 2020, (n.d.). https://www.who.int/director-general/speeches/detail/who-director-210

general-s-opening-remarks-at-the-media-briefing-on-covid-19---16-march-2020 (accessed January 211

13, 2022). 212

[2] R.W. Peeling, D.L. Heymann, Y.-Y. Teo, P.J. Garcia, Diagnostics for COVID-19: moving from pandemic 213

response to control., Lancet (London, England). (2021). https://doi.org/10.1016/S0140-214

6736(21)02346-1. 215

[3] European Commission Directorate-General for Health and Food Safety, EU health preparedness: A 216

common list of COVID-19 rapid antigen tests and a common standardised set of data to be included 217

in COVID-19 test result certificates, 2021. 218

https://ec.europa.eu/health/sites/default/files/preparedness_response/docs/covid-219

19_rat_common-list_en.pdf. 220

[4] V.M. Corman, V.C. Haage, T. Bleicker, M.L. Schmidt, B. Mühlemann, M. Zuchowski, W.K. Jo, P. 221

Tscheak, E. Möncke-Buchner, M.A. Müller, A. Krumbholz, J.F. Drexler, C. Drosten, Comparison of 222

seven commercial SARS-CoV-2 rapid point-of-care antigen tests: a single-centre laboratory 223

evaluation study., The Lancet. Microbe. 2 (2021) e311–e319. https://doi.org/10.1016/S2666-224

5247(21)00056-2. 225

[5] H. Scheiblauer, A. Filomena, A. Nitsche, A. Puyskens, V.M. Corman, C. Drosten, K. Zwirglmaier, C. 226

Lange, P. Emmerich, M. Müller, O. Knauer, C.M. Nübling, Comparative sensitivity evaluation for 122 227

CE-marked rapid diagnostic tests for SARS-CoV-2 antigen, Germany, September 2020 to April 2021., 228

Euro Surveill. Bull. Eur. Sur Les Mal. Transm. = Eur. Commun. Dis. Bull. 26 (2021). 229

https://doi.org/10.2807/1560-7917.ES.2021.26.44.2100441. 230

[6] F. Fitoussi, S. Tonen-Wolyec, N. Awaida, R. Dupont, L. Bélec, Analytical performance of the point-of-231

care BIOSYNEX COVID-19 Ag BSS for the detection of SARS-CoV-2 nucleocapsid protein in 232

nasopharyngeal swabs: a prospective field evaluation during the COVID-19 third wave in France., 233

Infection. (2021) 1–9. https://doi.org/10.1007/s15010-021-01723-5. 234

[7] G. Greub, G. Caruana, M. Schweitzer, M. Imperiali, V. Muigg, M. Risch, A. Croxatto, O. Opota, S. 235

Heller, D. Albertos Torres, M.-L. Tritten, K. Leuzinger, H.H. Hirsch, R. Lienhard, A. Egli, Multicenter 236

9

Technical Validation of 30 Rapid Antigen Tests for the Detection of SARS-CoV-2 (VALIDATE)., 237

Microorganisms. 9 (2021). https://doi.org/10.3390/microorganisms9122589. 238

[8] J.G. Routsias, M. Mavrouli, P. Tsoplou, K. Dioikitopoulou, A. Tsakris, Diagnostic performance of rapid 239

antigen tests (RATs) for SARS-CoV-2 and their efficacy in monitoring the infectiousness of COVID-19 240

patients., Sci. Rep. 11 (2021) 22863. https://doi.org/10.1038/s41598-021-02197-z. 241

[9] L.-T. Allan-Blitz, J.D. Klausner, A Real-World Comparison of SARS-CoV-2 Rapid Antigen Testing versus 242

PCR Testing in Florida., J. Clin. Microbiol. 59 (2021) e0110721. https://doi.org/10.1128/JCM.01107-243

21. 244

[10] D.A. Mistry, J.Y. Wang, M.-E. Moeser, T. Starkey, L.Y.W. Lee, A systematic review of the sensitivity 245

and specificity of lateral flow devices in the detection of SARS-CoV-2., BMC Infect. Dis. 21 (2021) 246

828. https://doi.org/10.1186/s12879-021-06528-3. 247

[11] L.E. Brümmer, S. Katzenschlager, M. Gaeddert, C. Erdmann, S. Schmitz, M. Bota, M. Grilli, J. 248

Larmann, M.A. Weigand, N.R. Pollock, A. Macé, S. Carmona, S. Ongarello, J.A. Sacks, C.M. Denkinger, 249

Accuracy of novel antigen rapid diagnostics for SARS-CoV-2: A living systematic review and meta-250

analysis., PLoS Med. 18 (2021) e1003735. https://doi.org/10.1371/journal.pmed.1003735. 251

[12] J. Dinnes, J.J. Deeks, S. Berhane, M. Taylor, A. Adriano, C. Davenport, S. Dittrich, D. Emperador, Y. 252

Takwoingi, J. Cunningham, S. Beese, J. Domen, J. Dretzke, L. Ferrante di Ruffano, I.M. Harris, M.J. 253

Price, S. Taylor-Phillips, L. Hooft, M.M. Leeflang, M.D. McInnes, R. Spijker, A. Van den Bruel, Rapid, 254

point-of-care antigen and molecular-based tests for diagnosis of SARS-CoV-2 infection., Cochrane 255

Database Syst. Rev. 3 (2021) CD013705. https://doi.org/10.1002/14651858.CD013705.pub2. 256

[13] A.K. Lindner, L.J. Krüger, O. Nikolai, J.A.F. Klein, H. Rössig, P. Schnitzler, V.M. Corman, T.C. Jones, F. 257

Tobian, M. Gaeddert, S. Burock, J.A. Sacks, J. Seybold, F.P. Mockenhaupt, C.M. Denkinger, SARS-CoV-258

2 Variant of Concern B.1.1.7: Diagnostic Sensitivity of Three Antigen-Detecting Rapid Tests., 259

Microbiol. Spectr. 10 (2022) e0076321. https://doi.org/10.1128/spectrum.00763-21. 260

[14] M. Bekliz, K. Adea, M. Essaidi-Laziosi, J.A. Sacks, C. Escadafal, L. Kaiser, I. Eckerle, SARS-CoV-2 rapid 261

diagnostic tests for emerging variants., The Lancet. Microbe. 2 (2021) e351. 262

https://doi.org/10.1016/S2666-5247(21)00147-6. 263

[15] T. Mohammad, A. Choudhury, I. Habib, P. Asrani, Y. Mathur, M. Umair, F. Anjum, A. Shafie, D.K. 264

Yadav, M.I. Hassan, Genomic Variations in the Structural Proteins of SARS-CoV-2 and Their 265

Deleterious Impact on Pathogenesis: A Comparative Genomics Approach, Front. Cell. Infect. 266

10

Microbiol. 11 (2021) 951. https://doi.org/10.3389/fcimb.2021.765039. 267

[16] I.W. Pray, L. Ford, D. Cole, C. Lee, J.P. Bigouette, G.R. Abedi, D. Bushman, M.J. Delahoy, D. Currie, B. 268

Cherney, M. Kirby, G. Fajardo, M. Caudill, K. Langolf, J. Kahrs, P. Kelly, C. Pitts, A. Lim, N. Aulik, A. 269

Tamin, J.L. Harcourt, K. Queen, J. Zhang, B. Whitaker, H. Browne, M. Medrzycki, P. Shewmaker, J. 270

Folster, B. Bankamp, M.D. Bowen, N.J. Thornburg, K. Goffard, B. Limbago, A. Bateman, J.E. Tate, D. 271

Gieryn, H.L. Kirking, R. Westergaard, M. Killerby, Performance of an Antigen-Based Test for 272

Asymptomatic and Symptomatic SARS-CoV-2 Testing at Two University Campuses - Wisconsin, 273

September-October 2020., MMWR. Morb. Mortal. Wkly. Rep. 69 (2021) 1642–1647. 274

https://doi.org/10.15585/mmwr.mm695152a3. 275

[17] S.L. Mitchell, S. Orris, T. Freeman, M.C. Freeman, M. Adam, M. Axe, J. Gribschaw, J. Suyama, A. 276

Hoberman, A. Wells, Performance of SARS-CoV-2 antigen testing in symptomatic and asymptomatic 277

adults: a single-center evaluation., BMC Infect. Dis. 21 (2021) 1071. 278

https://doi.org/10.1186/s12879-021-06716-1. 279

[18] E. Schuit, I.K. Veldhuijzen, R.P. Venekamp, W. van den Bijllaardt, S.D. Pas, E.B. Lodder, R. 280

Molenkamp, C.H. GeurtsvanKessel, J. Velzing, R.C. Huisman, L. Brouwer, T.L. Boelsums, G.J. Sips, 281

K.S.M. Benschop, L. Hooft, J.H.H.M. van de Wijgert, S. van den Hof, K.G.M. Moons, Diagnostic 282

accuracy of rapid antigen tests in asymptomatic and presymptomatic close contacts of individuals 283

with confirmed SARS-CoV-2 infection: cross sectional study., BMJ. 374 (2021) n1676. 284

https://doi.org/10.1136/bmj.n1676. 285

[19] L.J. Krüger, A. Tanuri, A.K. Lindner, M. Gaeddert, L. Köppel, F. Tobian, L.E. Brümmer, J.A.F. Klein, F. 286

Lainati, P. Schnitzler, O. Nikolai, F.P. Mockenhaupt, J. Seybold, V.M. Corman, T.C. Jones, C. Drosten, 287

C. Gottschalk, S.F. Weber, S. Weber, O.C. Ferreira, D. Mariani, E.R. Dos Santos Nascimento, T.M. 288

Pereira Pinto Castineiras, R.M. Galliez, D.S. Faffe, I. de C. Leitão, C. Dos Santos Rodrigues, T.S. 289

Frauches, K.J.C.V. Nocchi, N.M. Feitosa, S.S. Ribeiro, N.R. Pollock, B. Knorr, A. Welker, M. de Vos, J. 290

Sacks, S. Ongarello, C.M. Denkinger, Accuracy and ease-of-use of seven point-of-care SARS-CoV-2 291

antigen-detecting tests: A multi-centre clinical evaluation., EBioMedicine. 75 (2021) 103774. 292

https://doi.org/10.1016/j.ebiom.2021.103774. 293

[20] I. Wagenhäuser, K. Knies, V. Rauschenberger, M. Eisenmann, M. McDonogh, N. Petri, O. Andres, S. 294

Flemming, M. Gawlik, M. Papsdorf, R. Taurines, H. Böhm, J. Forster, D. Weismann, B. Weißbrich, L. 295

Dölken, J. Liese, O. Kurzai, U. Vogel, M. Krone, Clinical performance evaluation of SARS-CoV-2 rapid 296

antigen testing in point of care usage in comparison to RT-qPCR., EBioMedicine. 69 (2021) 103455. 297

11

https://doi.org/10.1016/j.ebiom.2021.103455. 298

[21] J.G. Schneider, Uffe Vest, Knudsen Jenny Dahl, Koch, Anders, Kirkby, Nikolai Søren, Lisby, A 299

prospective nationwide observational study of agreement of antigen tests on oral pharyngeal swabs 300

or less invasive testing with RT-qPCR, for detecting SARS-CoV-2 in adults: Protocol description, JMIR 301

Res. Protoc. (2022). http://dx.doi.org/10.2196/35706. 302

[22] M.W. Rosenstierne, S. Joshi, E.T. Danielsen, H. Webb, D.M. Luong, J. Bjerring, J. Hindkær, L. 303

Jørgensen, J. Blauenfeldt, A. Bojesen, F. Holck, J.W. Lau, L. Bangsgaard, J.B. Lind, M.B. Dragheim, 304

M.R. Jacobsen, R. Elkjær, S. Clauwaert, K. Christensen, C. Polacek, A. Fomsgaard, T. Ojalehto, A. 305

Tullila, M. Brummer, C.J. Jensen, F.H. Jensen, U.V. Schneider, J.G. Lisby, R.L. Jørgensen, T. Warthoe, 306

E. Finding, P. Warthoe, SARS-CoV-2 detection using reverse transcription strand invasion based 307

amplification and a portable compact size instrument., Sci. Rep. 11 (2021) 22214. 308

https://doi.org/10.1038/s41598-021-01744-y. 309

[23] A. Singanayagam, S. Hakki, J. Dunning, K.J. Madon, M.A. Crone, A. Koycheva, N. Derqui-Fernandez, 310

J.L. Barnett, M.G. Whitfield, R. Varro, A. Charlett, R. Kundu, J. Fenn, J. Cutajar, V. Quinn, E. Conibear, 311

W. Barclay, P.S. Freemont, G.P. Taylor, S. Ahmad, M. Zambon, N.M. Ferguson, A. Lalvani, Community 312

transmission and viral load kinetics of the SARS-CoV-2 delta (B.1.617.2) variant in vaccinated and 313

unvaccinated individuals in the UK: a prospective, longitudinal, cohort study., Lancet. Infect. Dis. 314

(2021). https://doi.org/10.1016/S1473-3099(21)00648-4. 315

316

RAT

Aco

n (

N; 0

.94

)

Lum

iraD

x (N

; 0.9

3)

Wo

nd

fo (

N; 0

.93

)

SD B

iose

nso

r (N

; 0.9

2)

DN

A d

iagn

ost

ics

(N;

0.9

1)

Fujir

ebio

(N

; 0.9

1)

Qia

gen

(N

; 0.9

0)

Qu

idel

(N

; 0.9

0)

Siem

ens

(N; 0

.90

)

Ro

che

(N; 0

.87

)

CTK

On

site

(N

; 0.8

6)

Bio

syn

ex A

g (N

; 0.8

4)

Fujir

ebio

(O

P; 0

.84

Szyb

io (

N; 0

.84

)

Qia

gen

(O

P; 0

.83

)B

D V

erit

or

(N v

isu

al;

0.8

1)

No

vira

l (N

; 0.8

1)

AU

H T

est

(N; 0

.80

)

Qu

idel

(O

P; 0

.80

)

Wh

ole

po

wer

(N

; 0.8

0)

Acr

o (

OP

; 0.7

9)

BD

Ver

ito

r (N

; 0.7

9)

Ab

bo

tt (

N; 0

.78

)B

iosy

nex

Ag+

(O

P;

0.7

7)

Viv

aDia

g (N

; 0.7

7)

AllT

est

(OP

; 0.7

6)

Litu

o (

N; 0

.75

)

Ap

i ph

arm

a (N

; 0.7

4)

Gen

sure

(N

; 0.7

4)

SD B

iose

nso

r (O

P; 0

.73

)

Qlif

e(N

; 0.7

2)

Ab

bo

tt (

OP

; 0.6

8)

Ro

che

(OP

; 0.6

9)

Szyb

io (

OP

; 0.6

5)

Siem

ens

(OP

; 0.6

5)

Wan

tai(

OP

; 0.5

9)

Acr

o (

S; 0

.49

)

Elys

ium

(O

P; 0

.48

)

Ap

i ph

arm

a(O

P; 0

.46

)

Qlif

e (O

P; 0

.32

)

No

vira

l (S;

0.2

9)

Szyb

io(S

; 0.1

9)

Wan

tai (

S; 0

.19

)

Elys

ium

(S;

0.1

3)

Litu

o(S

; 0.1

2)

LumiraDx (N; 0.92) *

Wondfo (N; 0.93)

SD Biosensor (N; 0.92) *

DNA diagnostics (N; 0.91) * *

Fujirebio (N; 0.91)

Qiagen (N; 0.90) *

Quidel (N; 0.90) * *

Siemens (N; 0.90) * *

Roche (N; 0.87)

CTK Onsite (N; 0.86)

Biosynex Ag (N; 0.84)

Fujirebio (OP; 0.84 * * *

Szybio (N; 0.84) *

Qiagen (OP; 0.83) * * * *

BD Veritor (N visual; 0.81) * * *

Noviral (N; 0.81)

AUH Test (N; 0.80) * *

Quidel (OP; 0.80)

Wholepower (N; 0.80)

Acro (OP; 0.79)

BD Veritor (N; 0.79)

Abbott (N; 0.78)

Biosynex Ag+ (OP; 0.77)

VivaDiag (N; 0.77)

AllTest (OP; 0.76)

Lituo (N; 0.75)

Api pharma (N; 0.74)

Gensure (N; 0.74)

SD Biosensor (OP; 0.73)

Qlife (N; 0.72)

Abbott (OP; 0.68)

Roche (OP; 0.69)

Szybio (OP; 0.65)

Siemens (OP; 0.65)

Wantai (OP; 0.59)

Acro (S; 0.49)

Elysium (OP; 0.48)

Api pharma (OP; 0.46)

Qlife (OP; 0.32)

Noviral (S; 0.29)

Szybio (S; 0.19)

Wantai (S; 0.19)

Elysium (S; 0.13)

Lituo (S; 0.12)

Quidel (S; 0.025)

Table 1 Comparison of clinical sensitivity between RAT. Green fields are non-significant differences, red are significant differences in clinical sensitivity. N anterior nasal cavity swabs,OP deep oropharyngeal swabs, S saliva. Sensitivity is reported in brackets. Details for calculation are included in Supplementary data.

Table 1 Click here to access/download;Table;Table 1.pptx

A Retrospective testing n=304

Cq <25, n=50 Cq 25-30, n=54 Cq 30-35, n=50 Cq >35, n=50RT-qPCR negative,

n=100

Abbott TP 22, FN 28, Inv 0 TP 12, FN 42, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Acon TP 38, FN 12, Inv 0 TP 17, FN 37, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Acro TP 50, FN 0, Inv 0 TP 33, FN 21, Inv 0 TP 3, FN 47, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 AllTest TP 47, FN 3, Inv 0 TP 35, FN 19, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Api pharma TP 38, FN 12, Inv 0 TP 13, FN 41, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 AUH Test TP 9, FN 41, Inv 0 TP 1, FN 53, Inv 0 TP 0, FN 50, Inv 0 TP 1, FN 49, Inv 0 TN 100, FP 0, Inv 0 BD Veritor TP 25, FN 25, Inv 0 TP 10, FN 44, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 BD Veritor N (visual) TP 25, FN 25, Inv 0 TP 9, FN 45, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Biosynex Ag TP 48, FN 2, Inv 0 TP 31, FN 23, Inv 0 TP 5, FN 45, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Biosynex Ag+ TP 41, FN 9, Inv 0 TP 13, FN 41, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 CTK Onsite TP 42, FN 8, Inv 0 TP 23, FN 31, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 DNA diagnostics TP 41, FN 5, Inv 4 TP 29, FN 25, Inv 0 TP 1, FN 49, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Fujirebio TP 50, FN 0, Inv 0 TP 31, FN 23, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Gensure TP 19, FN 31, Inv 0 TP 2, FN 52, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Lituo N TP 23, FN 27, Inv 0 TP 4, FN 50, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Lituo S TP 5, FN 45, Inv 0 TP 0, FN 54, Inv 0 TP 0, FN 49, Inv 1 TP 0, FN 49, Inv 1 TN 100, FP 0, Inv 0 LumiraDx TP 39, FN 11, Inv 0 TP 21, FN 33, Inv 0 TP 1, FN 49, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Noviral N TP 50, FN 0, Inv 0 TP 25, FN 29, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Noviral S TP 43, FN 7, Inv 0 TP 0, FN 54, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Qiagen TP 45, FN 5, Inv 0 TP 0, FN 54, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Qlife TP 50, FN 0, Inv 0 TP 50, FN 4, Inv 0 TP 30, FN 20, Inv 0 TP 6, FN 44, Inv 0 TN 93, FP 7, Inv 0 Quidel TP 37, FN 13, Inv 0 TP 16, FN 38, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Roche N TP 27, FN 23, Inv 0 TP 12, FN 42, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Roche OP TP 43, FN 7, Inv 0 TP 10, FN 43, Inv 1 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 SD Biosensor TP 40, FN 10, Inv 0 TP 12, FN 42, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 SD Biosensor OP TP 23, FN 27, Inv 0 TP 10, FN 44, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Siemens TP 44, FN 6, Inv 0 TP 20, FN 34, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Szybio TP 40, FN 10, Inv 0 TP 14, FN 40, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Szybio S TP 23, FN 27, Inv 0 TP 6, FN 48, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 VivaDiag TP 37, FN 13, Inv 0 TP 16, FN 38, Inv 0 TP 1 FN 49, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Wantai OP TP 40, FN 10, Inv 0 TP 23, FN 31, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Wantai S TP 42, FN 8, Inv 0 TP 21, FN 33, Inv 0 TP 1, FN 49, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Wholepower TP 14, FN 36, Inv 0 TP 7, FN 47, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Wondfo TP 43, FN 7, Inv 0 TP 25, FN 29, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0

Figure 1A Click here to access/download;Figure;Figure 1A STARD diagram.pptx

Included patients n = 3.797

Included SARS-CoV-2 previous positive n = 2.045

Screening at regional test center n = 1.752

RT-qPCR positive n = 1.893

RT-qPCR negativen = 140

RT-qPCR Invalid n = 12- Sample missing (n = 3)- Human control

negative (n = 9)

RT-qPCR positive n = 11

RT-qPCR negativen = 1.698

RT-qPCR Invalid n = 43- Sample missing (n = 8)- Human control

negative (n = 35)

TN 7, FP 0, Inv 0 TP 143, FN 64, Inv 1 Abbott (OP) n=390 TN 171, FP 0, Inv 0 TP 0, FN 4, Inv 0TN 6, FP 1, Inv 0 TP 163, FN 44, Inv 0 Abbott (N n=390 TN 169, FP 3, Inv 0 TP 0, FN 3, Inv 1TN 5, FP 0, Inv 0 TP 187, FN 12, Inv 0 Acon (N) n=414 TN 210, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 13, FP 1, Inv 0 TP 172, FN 46, Inv 0 Acro (OP) n=429 TN 196, FP 0, Inv 0 TP 0, FN 1, Inv 0TN 13, FP 1, Inv 0 TP 100, FN 106, Inv 12 Acro (S) n=428 TN 174, FP 1, Inv 20 TP 0, FN 1, Inv 0TN 31, FP 0, Inv 0 TP 155, FN 49, Inv 1 Alltest (OP) n=407 TN 169, FP 0, Inv 0 TP 1, FN 1, Inv 0TN 11, FP 0, Inv 0 TP 92, FN 109, Inv 4 Api pharma (OP) n=413 TN 196, FP 0, Inv 0 TP 1, FN 0, Inv 0TN 10, FP 1, Inv 0 TP 146, FN 53, Inv 6 Api pharma (N) n=412 TN 195, FP 0, Inv 0 TP 1, FN 0, Inv 0TN 7, FP 0, Inv 0 TP 145, FN 36, Inv 3 AUH Test (N) n=376 TN 184, FP 1, Inv 0 TP 0, FN 0, Inv 0TN 5, FP 0, Inv 0 TP 158, FN 41, Inv 0 BD Veritor (N) n=411 TN 207, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 5, FP 0, Inv 0 TP 165, FN 39, Inv 1 BD Veritor (N) vis n=422 TN 212, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 13, FP 1, Inv 0 TP 183, FN 35, Inv 0 Biosynex Ag (N) n=434 TN 201, FP 0, Inv 0 TP 0, FN 1, Inv 0TN 14, FP 0, Inv 0 TP 165, FN 51, Inv 0 Biosynex Ag+ (OP) n=414 TN 183, FP 0, Inv 0 TP 0, FN 1, Inv 0TN 9, FP 0, Inv 0 TP 184, FN 30, Inv 1 CTK onsite (N) n=420 TN 193, FP 0, Inv 2 TP 0, FN 1, Inv 0TN 23, FP 1, Inv 0 TP 202, FN 18, Inv 1 DNA diagnostic (N) n=418 TN 169, FP 0, Inv 0 TP 1, FN 1, Inv 2TN 7, FP 0, Inv 0 TP 101, FN 107, Inv 1 Elysium (OP) n=391 TN 171, FP 0, Inv 0 TP 1, FN 3, Inv 0TN 7, FP 0, Inv 0 TP 27, FN 179, Inv 3 Elysium (S) n=388 TN 167, FP 1, Inv 0 TP 0, FN 4, Inv 0TN 22, FP 0, Inv 0 TP 172, FN 30, Inv 0 Fujirebio (OP) n=465 TN 229, FP 0, Inv 10 TP 0, FN 2, Inv 0TN 22, FP 0, Inv 0 TP 183, FN 18, Inv 1 Fujirebio (N) n=441 TN 196, FP 0, Inv 19 TP 0, FN 1, Inv 1TN 13, FP 4, Inv 0 TP 150, FN 54, Inv 1 Gensure (N) n=424 TN 200, FP 0, Inv 1 TP 0, FN 1, Inv 0TN 13, FP 1, Inv 0 TP 160, FN 54, Inv 4 Lituo (N) n=450 TN 216, FP 0, Inv 2 TP 0, FN 0, Inv 0TN 13, FP 0, Inv 1 TP 26, FN 184, Inv 8 Lituo (S) n=447 TN 206, FP 2, Inv 7 TP 0, FN 0, Inv 0TN 5, FP 0, Inv 0 TP 193, FN 15, Inv 0 Lumiradx (N) n=416 TN 202, FP 0, Inv 0 TP 1, FN 0, Inv 0TN 6, FP 1, Inv 0 TP 169, FN 39, Inv 1 Noviral (N) n=389 TN 168, FP 1, Inv 0 TP 1, FN 1, Inv 2TN 7, FP 0, Inv 0 TP 59, FN 147, Inv 3 Noviral (S) n=384 TN 162, FP 1, Inv 1 TP 1, FN 3, Inv 0TN 21, FP 0, Inv 1 TP 167, FN 35, Inv 0 Qiagen (OP) n=430 TN 206, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 22, FP 0, Inv 0 TP 180, FN 21, Inv 1 Qiagen (N) n=430 TN 206, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 16, FP 1, Inv 0 TP 66, FN 142, Inv 0 Qlife (OP) n=389 TN 162, FP 2, Inv 0 TP 0, FN 0, Inv 0TN 11, FP 6, Inv 0 TP 150, FN 59, Inv 0 Qlife (N) n=447 TN 220, FP 1, Inv 0 TP 0, FN 0, Inv 0TN 5, FP 0, Inv 0 TP 160, FN 40, Inv 7 Quidel (OP) n=392 TN 176, FP 0, Inv 4 TP 0, FN 0, Inv 0TN 5, FP 0, Inv 0 TP 185, FN 20, Inv 3 Quidel (N) n=368 TN 145, FP 0, Inv 10 TP 0, FN 0, Inv 0TN 4, FP 1, Inv 0 TP 5, FN 199, Inv 3 Quidel (S) n=366 TN 146, FP 0, Inv 8 TP 0, FN 0, Inv 0TN 11, FP 0, Inv 0 TP 140, FN 65, Inv 0 Roche (OP) n=406 TN 190, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 10, FP 1, Inv 0 TP 177, FN 28, Inv 0 Roche (N) n=403 TN 187, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 24, FP 0, Inv 0 TP 162, FN 60, Inv 0 SD Biosensor (OP) n=441 TN 194, FP 0, Inv 0 TP 0, FN 1, Inv 0TN 22, FP 2, Inv 0 TP 204, FN 17, Inv 0 SD Biosensor (N) n=440 TN 194, FP 0, Inv 0 TP 0, FN 1, Inv 0TN 31, FP 0, Inv 0 TP 132, FN 72, Inv 1 Siemens (OP) n=407 TN 169, FP 0, Inv 0 TP 1, FN 1, Inv 0TN 22, FP 0, Inv 0 TP 182, FN 20, Inv 0 Siemens (N) n= 450 TN 225, FP 0, Inv 0 TP 0, FN 1, Inv 0TN 9, FP 0, Inv 0 TP 140, FN 75, Inv 0 Szybio (OP) n=411 TN 187, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 9, FP 0, Inv 0 TP 178, FN 34, Inv 3 Szybio (N) n=411 TN 187, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 9, FP 0, Inv 0 TP 40, FN 170, Inv 5 Szybio (S) n=396 TN 172, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 30, FP 0, Inv 0 TP 158, FN 47, Inv 0 VivaDiag (N) n=406 TN 166, FP 0, Inv 3 TP 1, FN 1, Inv 0TN 23, FP 1, Inv 0 TP 130, FN 91, Inv 1 Wantai (OP) n=469 TN 214, FP 3, Inv 4 TP 0, FN 2, Inv 0TN 23, FP 0, Inv 0 TP 39, FN 170, Inv 0 Wantai (S) n=449 TN 206, FP 2, Inv 7 TP 0, FN 2, Inv 0TN 6, FP 1, Inv 0 TP 166, FN 41, Inv 1 Wholepower (N) n=417 TN 200, FP 0, Inv 1 TP 0, FN 1, Inv 0TN 21, FP 2, Inv 1 TP 204, FN 14, Inv 3 Wondfo (N) n=468 TN 217, FP 0, Inv 4 TP 0, FN 2, Inv 0

B

Figure 1 STARD diagram. A, retrospective study part reporting RAT results compared to RT-qPCR stratified into Cq ranges. B, pro-spective clinical study part reporting data from individuals, who were either included due to a positive RT-qPCR test for SARS-CoV-2 or being tested as part of screening for SARS-CoV-2. For each RAT the total number of tests is reported together with the distribution compared to RT-qPCR. FN false negative, FP false positive, Inv invalid RAT, TN true negative, TP true positive. N anterior nasal cavity sampling, OP deep oropharyngeal sampling, S saliva.

Figure 1B Click here to access/download;Figure;Figure 1B STARD diagram.pptx

Qlife Acro

Biosynex Ag AllTest

FujirebioNoviral N

DNA diagnosticsWondfo

CTK OnsiteWantai OP

Wantai SSiemens

QiagenLumiraDx

Acon Biosynex Ag+

Noviral SRoche OPVivaDiag

Szybio Quidel

SD BiosensorApi pharma

Roche NAbbott

BD Veritor BD Veritor N (vis)SD Biosensor OP

Szybio SLituo N

Gensure Wholepower

AUH Test Lituo S

RAT0.67 [0.60-0.73]0.42 [0.35-0.49]0.41 [0.34-0.48]0.40 [0.34-0.47]0.40 [0.33-0.46]0.37 [0.30-0.44]0.35 [0.29-0.42]0.33 [0.27-0.40]0.32 [0.26-0.38]0.31 [0.25-0.37]0.31 [0.25-0.38]0.31 [0.25-0.38]0.30 [0.23-0.36]0.30 [0.24-0.36]0.27 [0.21-0.33]0.26 [0.20-0.33]0.26 [0.21-0.33]0.26 [0.20-0.33]0.26 [0.21-0.33]0.26 [0.20-0.33]0.26 [0.20-0.32]0.25 [0.20-0.32]0.25 [0.19-0.31]0.19 [0.14-0.24]0.17 [0.11-0.22]0.17 [0.12-0.22]0.17 [0.11-0.22]0.16 [0.11-0.21]0.14 [0.10-0.19]0.13 [0.09-0.18]0.10 [0.06-0.15]0.10 [0.06-0.15]0.05 [0.03-0.09]0.03 [0.01-0.05]

Sensitivity [95%CI]

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

Sensitivity

Overall analytical sensitivity, n = 204

Figure 2 Click here to access/download;Figure;Figure 2 JCV.docx

Figure 2 Overall analytical sensitivity and specificity of 33 RAT and one SIBA-rt-PCR test. Sensitivity and specificity are reported as mean with 95% CI

and is based on 50 samples with Cq <25, 54 samples with Cq between 25 to 30, 50 samples with Cq between 30 to 35 and 50 samples with Cq >35 by

RT-qPCR.

Qlife Acro

Biosynex Ag AllTest

FujirebioNoviral N

DNA diagnosticsWondfo

CTK OnsiteWantai OP

Wantai SSiemens

QiagenLumiraDx

Acon Biosynex Ag+

Noviral SRoche OPVivaDiag

Szybio Quidel

SD BiosensorApi pharma

Roche NAbbott

BD Veritor BD Veritor N (vis)SD Biosensor OP

Szybio SLituo N

Gensure Wholepower

AUH Test Lituo S

RAT0.93 [0.88-0.98]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]

Specificity [95%CI]

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Specificity

Overall analytical specificity, n = 100

Acon N (ST)LumiraDx N (I)

Wondfo NSD Biosensor N

DNA diagnostics N (ST)Fujirebio N

Qiagen N Quidel N (I)Siemens N

Roche NCTK Onsite N

Biosynex Ag NFujirebio OP

Szybio NQiagen OP

BD Veritor N (visual)Noviral N

AUH Test N (ST)Quidel OP (I)

Wholepower NAcro OP

BD Veritor N (I)Abbott N

Biosynex Ag+ OPVivaDiag NAllTest OP

Lituo NApi pharma N

Gensure NSD Biosensor OP

Qlife N (I)Abbott OPRoche OPSzybio OP

Siemens OPWantai OP

Acro SElysium OP

Api pharma OPQlife OP (I)

Noviral SSzybio S

Wantai S (ST)Elysium S

Lituo SQuidel S (I)

RAT0.94 [0.91-0.97]0.93 [0.89-0.96]0.93 [0.89-0.96]0.92 [0.88-0.95]0.91 [0.88-0.95]0.91 [0.86-0.94]0.90 [0.85-0.94]0.90 [0.86-0.94]0.90 [0.85-0.94]0.87 [0.82-0.91]0.86 [0.81-0.90]0.84 [0.79-0.88]0.84 [0.79-0.89]0.84 [0.79-0.89]0.83 [0.78-0.88]0.81 [0.75-0.86]0.81 [0.76-0.86]0.80 [0.74-0.85]0.80 [0.75-0.86]0.80 [0.74-0.85]0.79 [0.74-0.85]0.79 [0.74-0.85]0.78 [0.72-0.83]0.77 [0.71-0.82]0.77 [0.71-0.82]0.76 [0.70-0.81]0.75 [0.70-0.81]0.74 [0.68-0.80]0.74 [0.67-0.79]0.73 [0.67-0.79]0.72 [0.66-0.78]0.68 [0.61-0.74]0.68 [0.62-0.75]0.65 [0.59-0.71]0.64 [0.58-0.71]0.59 [0.52-0.65]0.49 [0.42-0.55]0.48 [0.41-0.55]0.46 [0.39-0.53]0.32 [0.26-0.38]0.29 [0.23-0.34]0.19 [0.14-0.24]0.19 [0.14-0.24]0.13 [0.08-0.18]0.12 [0.08-0.17]0.03 [0.01-0.05]

Sensitivity [95%CI]

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Sensitivity

Overall clinical sensitivity

Figure 3 Click here to access/download;Figure;Figure 3 JCV.docx

Figure 3 Overall clinical sensitivity and specificity of 44 RAT and two SIBA-rt-PCR tests. Sensitivity and specificity are reported as mean with 95% CI. N

are anterior nasal cavity swabs, OP are deep oropharyngeal swabs and S are saliva based RAT. ST are self-test, I are instrument read-out tests and

visual means that the RAT was evaluated visually instead of by instrumental read-out.

Acon N (ST)LumiraDx N (I)

Wondfo NSD Biosensor N

DNA diagnostics N (ST)Fujirebio N

Qiagen N Quidel N (I)Siemens N

Roche NCTK Onsite N

Biosynex Ag NFujirebio OP

Szybio NQiagen OP

BD Veritor N (visual)Noviral N

AUH Test N (ST)Quidel OP (I)

Wholepower NAcro OP

BD Veritor N (I)Abbott N

Biosynex Ag+ OPVivaDiag NAllTest OP

Lituo NApi pharma N

Gensure NSD Biosensor OP

Qlife N (I)Abbott OPRoche OPSzybio OP

Siemens OPWantai OP

Acro SElysium OP

Api pharma OPQlife OP (I)

Noviral SSzybio S

Wantai S (ST)Elysium S

Lituo SQuidel S (I)

RAT1.00 [1.00-1.00]1.00 [1.00-1.00]0.99 [0.97-1.00]0.99 [0.97-1.00]0.99 [0.97-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]0.99 [0.98-1.00]1.00 [1.00-1.00]0.99 [0.98-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]0.99 [0.97-1.00]0.99 [0.98-1.00]1.00 [1.00-1.00]1.00 [0.98-1.00]1.00 [0.99-1.00]1.00 [1.00-1.00]0.98 [0.95-0.99]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [0.99-1.00]1.00 [0.98-1.00]0.98 [0.96-1.00]1.00 [1.00-1.00]0.97 [0.95-0.99]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]0.98 [0.97-1.00]0.99 [0.97-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]0.98 [0.96-1.00]0.99 [0.98-1.00]1.00 [1.00-1.00]0.99 [0.98-1.00]0.99 [0.98-1.00]0.99 [0.98-1.00]0.99 [0.98-1.00]

Specificity [95%CI]

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Specificity

Overall clinical specificity

Supplementary Data

Click here to access/downloadSupplementary Data

Supplementary data 20220211.docx