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      Ten rapid antigen tests for SARS-CoV-2 widely differ in their ability to detect Omicron-BA.4 and -BA.5

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          Abstract

          Since late 2021, the variant landscape of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been dominated by the variant of concern (VoC) Omicron and its sublineages. We and others have shown that the detection of Omicron-BA.1 and -BA.2-positive respiratory specimens by rapid antigen tests (RATs) is impaired compared to Delta VoC-containing samples. Here, in a single-center retrospective laboratory study, we evaluated the performance of ten most commonly used RATs for the detection of Omicron-BA.4 and -BA.5 infections. We used 171 respiratory swab specimens from SARS-CoV-2 RNA-positive patients, of which 71 were classified as BA.4 and 100 as BA.5. All swabs were collected between July and September 2022. 50 SARS-CoV-2 PCR-negative samples from healthy individuals, collected in October 2022, showed high specificity in 9 out of 10 RATs. When assessing analytical sensitivity using clinical specimens, the 50% limit of detection (LoD50) ranged from 7.6 × 10 4 to 3.3 × 10 6 RNA copies subjected to the RATs for BA.4 compared to 6.8 × 10 4 to 3.0 × 10 6 for BA.5. Overall, intra-assay differences for the detection of these two Omicron subvariants were not significant for both respiratory swabs and tissue culture-expanded virus isolates. In contrast, marked heterogeneity was observed among the ten RATs: to be positive in these point-of-care tests, up to 443-fold (BA.4) and up to 56-fold (BA.5) higher viral loads were required for the worst performing RAT compared to the best performing RAT. True-positive rates for Omicron-BA.4- or -BA.5-containing specimens in the highest viral load category ( C t values < 25) ranged from 94.3 to 34.3%, dropping to 25.6 to 0% for samples with intermediate C t values (25–30). We conclude that the high heterogeneity in the performance of commonly used RATs remains a challenge for the general public to obtain reliable results in the evolving Omicron subvariant-driven pandemic.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s00430-023-00775-8.

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          SARS-CoV-2 variant biology: immune escape, transmission and fitness

          In late 2020, after circulating for almost a year in the human population, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exhibited a major step change in its adaptation to humans. These highly mutated forms of SARS-CoV-2 had enhanced rates of transmission relative to previous variants and were termed ‘variants of concern’ (VOCs). Designated Alpha, Beta, Gamma, Delta and Omicron, the VOCs emerged independently from one another, and in turn each rapidly became dominant, regionally or globally, outcompeting previous variants. The success of each VOC relative to the previously dominant variant was enabled by altered intrinsic functional properties of the virus and, to various degrees, changes to virus antigenicity conferring the ability to evade a primed immune response. The increased virus fitness associated with VOCs is the result of a complex interplay of virus biology in the context of changing human immunity due to both vaccination and prior infection. In this Review, we summarize the literature on the relative transmissibility and antigenicity of SARS-CoV-2 variants, the role of mutations at the furin spike cleavage site and of non-spike proteins, the potential importance of recombination to virus success, and SARS-CoV-2 evolution in the context of T cells, innate immunity and population immunity. SARS-CoV-2 shows a complicated relationship among virus antigenicity, transmission and virulence, which has unpredictable implications for the future trajectory and disease burden of COVID-19.
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            Comparison of seven commercial SARS-CoV-2 rapid point-of-care antigen tests: a single-centre laboratory evaluation study

            Background Antigen point-of-care tests (AgPOCTs) can accelerate SARS-CoV-2 testing. As some AgPOCTs have become available, interest is growing in their utility and performance. Here we aimed to compare the analytical sensitivity and specificity of seven commercially available AgPOCT devices. Methods In a single-centre, laboratory evaluation study, we compared AgPOCT products from seven suppliers: the Abbott Panbio COVID-19 Ag Rapid Test, the RapiGEN BIOCREDIT COVID-19 Ag, the Healgen Coronavirus Ag Rapid Test Cassette (Swab), the Coris BioConcept COVID-19 Ag Respi-Strip, the R-Biopharm RIDA QUICK SARS-CoV-2 Antigen, the nal von minden NADAL COVID-19 Ag Test, and the Roche-SD Biosensor SARS-CoV Rapid Antigen Test. Tests were evaluated on recombinant SARS-CoV-2 nucleoprotein, cultured endemic and emerging coronaviruses, stored respiratory samples with known SARS-CoV-2 viral loads, stored samples from patients with respiratory pathogens other than SARS-CoV-2, and self-sampled swabs from healthy volunteers. We estimated analytical sensitivity in terms of approximate viral concentrations (quantified by real-time RT-PCR) that yielded positive AgPOCT results, and specificity in terms of propensity to generate false-positive results. Findings In 138 clinical samples with quantified SARS-CoV-2 viral load, the 95% limit of detection (concentration at which 95% of test results were positive) in six of seven AgPOCT products ranged between 2·07 × 106 and 2·86 × 107 copies per swab, with an outlier (RapiGEN) at 1·57 × 1010 copies per swab. The assays showed no cross-reactivity towards cell culture or tissue culture supernatants containing any of the four endemic human coronaviruses (HCoV‑229E, HCoV‑NL63, HCoV‑OC43, or HCoV‑HKU1) or MERS-CoV, with the exception of the Healgen assay in one repeat test on HCoV-HKU1 supernatant. SARS-CoV was cross-detected by all assays. Cumulative specificities among stored clinical samples with non-SARS-CoV-2 infections (n=100) and self-samples from healthy volunteers (n=35; cumulative sample n=135) ranged between 98·5% (95% CI 94·2–99·7) and 100·0% (97·2–100·0) in five products, with two outliers at 94·8% (89·2–97·7; R-Biopharm) and 88·9% (82·1–93·4; Healgen). False-positive results did not appear to be associated with any specific respiratory pathogen. Interpretation The sensitivity range of most AgPOCTs overlaps with SARS-CoV-2 viral loads typically observed in the first week of symptoms, which marks the infectious period in most patients. The AgPOCTs with limit of detections that approximate virus concentrations at which patients are infectious might enable shortcuts in decision making in various areas of health care and public health. Funding EU's Horizon 2020 research and innovation programme, German Ministry of Research, German Federal Ministry for Economic Affairs and Energy, German Ministry of Health, and Bill & Melinda Gates Foundation.
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              Rapid, point‐of‐care antigen tests for diagnosis of SARS‐CoV‐2 infection

              Abstract Background Accurate rapid diagnostic tests for SARS‐CoV‐2 infection would be a useful tool to help manage the COVID‐19 pandemic. Testing strategies that use rapid antigen tests to detect current infection have the potential to increase access to testing, speed detection of infection, and inform clinical and public health management decisions to reduce transmission. This is the second update of this review, which was first published in 2020. Objectives To assess the diagnostic accuracy of rapid, point‐of‐care antigen tests for diagnosis of SARS‐CoV‐2 infection. We consider accuracy separately in symptomatic and asymptomatic population groups. Sources of heterogeneity investigated included setting and indication for testing, assay format, sample site, viral load, age, timing of test, and study design. Search methods We searched the COVID‐19 Open Access Project living evidence database from the University of Bern (which includes daily updates from PubMed and Embase and preprints from medRxiv and bioRxiv) on 08 March 2021. We included independent evaluations from national reference laboratories, FIND and the Diagnostics Global Health website. We did not apply language restrictions. Selection criteria We included studies of people with either suspected SARS‐CoV‐2 infection, known SARS‐CoV‐2 infection or known absence of infection, or those who were being screened for infection. We included test accuracy studies of any design that evaluated commercially produced, rapid antigen tests. We included evaluations of single applications of a test (one test result reported per person) and evaluations of serial testing (repeated antigen testing over time). Reference standards for presence or absence of infection were any laboratory‐based molecular test (primarily reverse transcription polymerase chain reaction (RT‐PCR)) or pre‐pandemic respiratory sample. Data collection and analysis We used standard screening procedures with three people. Two people independently carried out quality assessment (using the QUADAS‐2 tool) and extracted study results. Other study characteristics were extracted by one review author and checked by a second. We present sensitivity and specificity with 95% confidence intervals (CIs) for each test, and pooled data using the bivariate model. We investigated heterogeneity by including indicator variables in the random‐effects logistic regression models. We tabulated results by test manufacturer and compliance with manufacturer instructions for use and according to symptom status. Main results We included 155 study cohorts (described in 166 study reports, with 24 as preprints). The main results relate to 152 evaluations of single test applications including 100,462 unique samples (16,822 with confirmed SARS‐CoV‐2). Studies were mainly conducted in Europe (101/152, 66%), and evaluated 49 different commercial antigen assays. Only 23 studies compared two or more brands of test. Risk of bias was high because of participant selection (40, 26%); interpretation of the index test (6, 4%); weaknesses in the reference standard for absence of infection (119, 78%); and participant flow and timing 41 (27%). Characteristics of participants (45, 30%) and index test delivery (47, 31%) differed from the way in which and in whom the test was intended to be used. Nearly all studies (91%) used a single RT‐PCR result to define presence or absence of infection. The 152 studies of single test applications reported 228 evaluations of antigen tests. Estimates of sensitivity varied considerably between studies, with consistently high specificities. Average sensitivity was higher in symptomatic (73.0%, 95% CI 69.3% to 76.4%; 109 evaluations; 50,574 samples, 11,662 cases) compared to asymptomatic participants (54.7%, 95% CI 47.7% to 61.6%; 50 evaluations; 40,956 samples, 2641 cases). Average sensitivity was higher in the first week after symptom onset (80.9%, 95% CI 76.9% to 84.4%; 30 evaluations, 2408 cases) than in the second week of symptoms (53.8%, 95% CI 48.0% to 59.6%; 40 evaluations, 1119 cases). For those who were asymptomatic at the time of testing, sensitivity was higher when an epidemiological exposure to SARS‐CoV‐2 was suspected (64.3%, 95% CI 54.6% to 73.0%; 16 evaluations; 7677 samples, 703 cases) compared to where COVID‐19 testing was reported to be widely available to anyone on presentation for testing (49.6%, 95% CI 42.1% to 57.1%; 26 evaluations; 31,904 samples, 1758 cases). Average specificity was similarly high for symptomatic (99.1%) or asymptomatic (99.7%) participants. We observed a steady decline in summary sensitivities as measures of sample viral load decreased. Sensitivity varied between brands. When tests were used according to manufacturer instructions, average sensitivities by brand ranged from 34.3% to 91.3% in symptomatic participants (20 assays with eligible data) and from 28.6% to 77.8% for asymptomatic participants (12 assays). For symptomatic participants, summary sensitivities for seven assays were 80% or more (meeting acceptable criteria set by the World Health Organization (WHO)). The WHO acceptable performance criterion of 97% specificity was met by 17 of 20 assays when tests were used according to manufacturer instructions, 12 of which demonstrated specificities above 99%. For asymptomatic participants the sensitivities of only two assays approached but did not meet WHO acceptable performance standards in one study each; specificities for asymptomatic participants were in a similar range to those observed for symptomatic people. At 5% prevalence using summary data in symptomatic people during the first week after symptom onset, the positive predictive value (PPV) of 89% means that 1 in 10 positive results will be a false positive, and around 1 in 5 cases will be missed. At 0.5% prevalence using summary data for asymptomatic people, where testing was widely available and where epidemiological exposure to COVID‐19 was suspected, resulting PPVs would be 38% to 52%, meaning that between 2 in 5 and 1 in 2 positive results will be false positives, and between 1 in 2 and 1 in 3 cases will be missed. Authors' conclusions Antigen tests vary in sensitivity. In people with signs and symptoms of COVID‐19, sensitivities are highest in the first week of illness when viral loads are higher. Assays that meet appropriate performance standards, such as those set by WHO, could replace laboratory‐based RT‐PCR when immediate decisions about patient care must be made, or where RT‐PCR cannot be delivered in a timely manner. However, they are more suitable for use as triage to RT‐PCR testing. The variable sensitivity of antigen tests means that people who test negative may still be infected. Many commercially available rapid antigen tests have not been evaluated in independent validation studies. Evidence for testing in asymptomatic cohorts has increased, however sensitivity is lower and there is a paucity of evidence for testing in different settings. Questions remain about the use of antigen test‐based repeat testing strategies. Further research is needed to evaluate the effectiveness of screening programmes at reducing transmission of infection, whether mass screening or targeted approaches including schools, healthcare setting and traveller screening.
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                Author and article information

                Contributors
                krenn@mvp.lmu.de
                daechert@mvp.lmu.de
                badell@mvp.lmu.de
                Lupoli@mvp.lmu.de
                gamzenaz.oztan@hotmail.com
                t.feng@campus.lmu.de
                Schneider.Nikolas@web.de
                melanie.huber@mvp.lmu.de
                autenrieth@mvp.lmu.de
                pspaeth@mvp.lmu.de
                muenchhoff@mvp.lmu.de
                graf@genzentrum.lmu.de
                krebs@genzentrum.lmu.de
                blum@genzentrum.lmu.de
                J.Durner@labor-becker.de
                L.Czibere@labor-becker.de
                lars.kaderali@uni-greifswald.de
                keppler@mvp.lmu.de
                baldauf@mvp.lmu.de
                osterman@mvp.lmu.de
                Journal
                Med Microbiol Immunol
                Med Microbiol Immunol
                Medical Microbiology and Immunology
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0300-8584
                1432-1831
                10 August 2023
                10 August 2023
                2023
                : 212
                : 5
                : 323-337
                Affiliations
                [1 ]GRID grid.5252.0, ISNI 0000 0004 1936 973X, Max von Pettenkofer Institute & Gene Center, Virology, , National Reference Center for Retroviruses, LMU München, ; Munich, Germany
                [2 ]GRID grid.452463.2, German Center for Infection Research (DZIF), Partner Site, ; Munich, Germany
                [3 ]GRID grid.5252.0, ISNI 0000 0004 1936 973X, COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, , LMU München, ; Munich, Germany
                [4 ]GRID grid.5252.0, ISNI 0000 0004 1936 973X, Laboratory for Functional Genome Analysis, Gene Center, , LMU München, ; Munich, Germany
                [5 ]Labor Becker MVZ GbR, Munich, Germany
                [6 ]GRID grid.5603.0, Institute of Bioinformatics, , University Medicine Greifswald, ; Greifswald, Germany
                Author notes

                Edited by: Matthias J. Reddehase.

                Author information
                http://orcid.org/0000-0001-5435-5972
                Article
                775
                10.1007/s00430-023-00775-8
                10501931
                37561225
                5ad075af-840f-4c86-a8a5-503a1b2fadd7
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 March 2023
                : 11 July 2023
                Funding
                Funded by: Bay-VOC
                Funded by: FOR-COVID
                Funded by: Ludwig-Maximilians-Universität München (1024)
                Categories
                Original Investigation
                Custom metadata
                © Springer-Verlag GmbH Germany, part of Springer Nature 2023

                Microbiology & Virology
                sars-cov-2 rapid antigen test,nucleocapsid protein,diagnostic test,sensitivity,specificity,voc,lateral flow,omicron

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