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Bottino P, Pizzo V, Castaldo S, Scomparin E, Bara C, Cerrato M, Sisinni S, Penpa S, Roveta A, Gerbino M, Maconi A, Rocchetti A. Clinical Evaluation and Comparison of Two Microfluidic Antigenic Assays for Detection of SARS-CoV-2 Virus. Microorganisms 2023; 11:2709. [PMID: 38004721 PMCID: PMC10673207 DOI: 10.3390/microorganisms11112709] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 10/27/2023] [Accepted: 11/03/2023] [Indexed: 11/26/2023] Open
Abstract
Given the ongoing pandemic, there is a need to identify SARS-CoV-2 and differentiate it from other respiratory viral infections in various critical settings. Since its introduction, rapid antigen testing is spreading worldwide, but diagnostic accuracy is extremely variable and often in disagreement with the manufacturer's specifications. Our study compared the clinical performances of two microfluidic rapid antigen tests towards a molecular assay, starting from positive samples. A total of 151 swabs collected at the Microbiology and Virology Laboratory of A.O. "SS Antonio e Biagio e C. Arrigo" (Alessandria, Italy) for the diagnosis of SARS-CoV-2 were simultaneously tested to evaluate accuracy, specificity, and agreement with the RT-qPCR results. Both assays showed an overall agreement of 100% for negative specimens, while positive accuracy comprised between 45.10% and 54.90%. According to the manufacturer's instructions, the greatest correlation between the antigenic and molecular assays was observed for the subset with high viral load (18/19, 94.74%), while it dramatically decreased for other subsets. Moreover, the ability to differentiate between SARS-CoV-2 and Flu provides an added value and could be addressed in an epidemic context. However, an in-house validation should be performed due to differences observed in performance declared by manufacturers and those actually obtained.
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Affiliation(s)
- Paolo Bottino
- Microbiology and Virology Laboratory, A.O. “SS Antonio e Biagio e C. Arrigo”, Via Venezia 16, 15121 Alessandria, Italy; (V.P.); (S.C.); (E.S.); (C.B.); (M.C.); (A.R.)
| | - Valentina Pizzo
- Microbiology and Virology Laboratory, A.O. “SS Antonio e Biagio e C. Arrigo”, Via Venezia 16, 15121 Alessandria, Italy; (V.P.); (S.C.); (E.S.); (C.B.); (M.C.); (A.R.)
| | - Salvatore Castaldo
- Microbiology and Virology Laboratory, A.O. “SS Antonio e Biagio e C. Arrigo”, Via Venezia 16, 15121 Alessandria, Italy; (V.P.); (S.C.); (E.S.); (C.B.); (M.C.); (A.R.)
| | - Elisabetta Scomparin
- Microbiology and Virology Laboratory, A.O. “SS Antonio e Biagio e C. Arrigo”, Via Venezia 16, 15121 Alessandria, Italy; (V.P.); (S.C.); (E.S.); (C.B.); (M.C.); (A.R.)
| | - Cristina Bara
- Microbiology and Virology Laboratory, A.O. “SS Antonio e Biagio e C. Arrigo”, Via Venezia 16, 15121 Alessandria, Italy; (V.P.); (S.C.); (E.S.); (C.B.); (M.C.); (A.R.)
| | - Marcella Cerrato
- Microbiology and Virology Laboratory, A.O. “SS Antonio e Biagio e C. Arrigo”, Via Venezia 16, 15121 Alessandria, Italy; (V.P.); (S.C.); (E.S.); (C.B.); (M.C.); (A.R.)
| | - Sabrina Sisinni
- Research and Innovation Department (DAIRI), A.O. “SS. Antonio e Biagio e C. Arrigo”, Via Venezia 16, 15121 Alessandria, Italy; (S.S.); (S.P.); (A.R.); (A.M.)
| | - Serena Penpa
- Research and Innovation Department (DAIRI), A.O. “SS. Antonio e Biagio e C. Arrigo”, Via Venezia 16, 15121 Alessandria, Italy; (S.S.); (S.P.); (A.R.); (A.M.)
| | - Annalisa Roveta
- Research and Innovation Department (DAIRI), A.O. “SS. Antonio e Biagio e C. Arrigo”, Via Venezia 16, 15121 Alessandria, Italy; (S.S.); (S.P.); (A.R.); (A.M.)
| | - Maria Gerbino
- Department of Science and Technological Innovation (DISIT), University of Eastern Piedmont, Viale Teresa Michel 11, 15121 Alessandria, Italy;
| | - Antonio Maconi
- Research and Innovation Department (DAIRI), A.O. “SS. Antonio e Biagio e C. Arrigo”, Via Venezia 16, 15121 Alessandria, Italy; (S.S.); (S.P.); (A.R.); (A.M.)
| | - Andrea Rocchetti
- Microbiology and Virology Laboratory, A.O. “SS Antonio e Biagio e C. Arrigo”, Via Venezia 16, 15121 Alessandria, Italy; (V.P.); (S.C.); (E.S.); (C.B.); (M.C.); (A.R.)
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Krenn F, Dächert C, Badell I, Lupoli G, Öztan GN, Feng T, Schneider N, Huber M, Both H, Späth PM, Muenchhoff M, Graf A, Krebs S, Blum H, Durner J, Czibere L, Kaderali L, Keppler OT, Baldauf HM, Osterman A. Ten rapid antigen tests for SARS-CoV-2 widely differ in their ability to detect Omicron-BA.4 and -BA.5. Med Microbiol Immunol 2023; 212:323-337. [PMID: 37561225 PMCID: PMC10501931 DOI: 10.1007/s00430-023-00775-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 07/11/2023] [Indexed: 08/11/2023]
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 × 104 to 3.3 × 106 RNA copies subjected to the RATs for BA.4 compared to 6.8 × 104 to 3.0 × 106 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 (Ct values < 25) ranged from 94.3 to 34.3%, dropping to 25.6 to 0% for samples with intermediate Ct 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.
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Affiliation(s)
- Franziska Krenn
- Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Christopher Dächert
- Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany
| | - Irina Badell
- Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Gaia Lupoli
- Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Gamze Naz Öztan
- Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Tianle Feng
- Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Nikolas Schneider
- Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Melanie Huber
- Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Hanna Both
- Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Patricia M. Späth
- Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Maximilian Muenchhoff
- Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany
- COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, LMU München, Munich, Germany
| | - Alexander Graf
- Laboratory for Functional Genome Analysis, Gene Center, LMU München, Munich, Germany
| | - Stefan Krebs
- Laboratory for Functional Genome Analysis, Gene Center, LMU München, Munich, Germany
| | - Helmut Blum
- Laboratory for Functional Genome Analysis, Gene Center, LMU München, Munich, Germany
| | | | | | - Lars Kaderali
- Institute of Bioinformatics, University Medicine Greifswald, Greifswald, Germany
| | - Oliver T. Keppler
- Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany
- COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, LMU München, Munich, Germany
| | - Hanna-Mari Baldauf
- Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Andreas Osterman
- Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
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Golden A, Cantera JL, Lillis L, Phan TT, Slater H, Webb EJ, Peck RB, Boyle DS, Domingo GJ. A Reagent and Virus Benchmarking Panel for a Uniform Analytical Performance Assessment of N Antigen-Based Diagnostic Tests for COVID-19. Microbiol Spectr 2023; 11:e0373122. [PMID: 37166329 PMCID: PMC10269465 DOI: 10.1128/spectrum.03731-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 04/21/2023] [Indexed: 05/12/2023] Open
Abstract
Rapid diagnostic tests (RDTs) that detect antigen indicative of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection can help in making quick health care decisions and regularly monitoring groups at risk of infection. With many RDT products entering the market, it is important to rapidly evaluate their relative performance. Comparison of clinical evaluation study results is challenged by protocol design variations and study populations. Laboratory assays were developed to quantify nucleocapsid (N) and spike (S) SARS-CoV-2 antigens. Quantification of the two antigens in nasal eluates confirmed higher abundance of N than S antigen. The median concentration of N antigen was 10 times greater than S per genome equivalent. The N antigen assay was used in combination with quantitative reverse transcription (RT)-PCR to qualify a panel composed of recombinant antigens, inactivated virus, and clinical specimen pools. This benchmarking panel was applied to evaluate the analytical performance of the SD Biosensor Standard Q COVID-19 antigen (Ag) test, Abbott Panbio COVID-19 Ag rapid test, Abbott BinaxNOW COVID-19 Ag test, and the LumiraDx SARS-CoV-2 Ag test. The four tests displayed different sensitivities toward the different panel members, but all performed best with the clinical specimen pool. The concentration for a 90% probability of detection across the four tests ranged from 21 to 102 pg/mL of N antigen in the extracted sample. Benchmarking panels provide a quick way to verify the baseline performance of a diagnostic and enable direct comparisons between diagnostic tests. IMPORTANCE This study reports the results for severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) nucleocapsid (N) and spike (S) antigen quantification assays and their performance against clinical reverse transcription (RT)-PCR results, thus describing an open-access quantification method for two important SARS-CoV-2 protein analytes. Characterized N antigen panels were used to evaluate the limits of detection of four different rapid tests for SARS-CoV-2 against multiple sources of nucleocapsid antigen, demonstrating proof-of-concept materials and methodology to evaluate SARS-CoV-2 rapid antigen detection tests. Quantification of N antigen was used to characterize the relationship between viral count and antigen concentration among clinical samples and panel members of both clinical sample and viral culture origin. This contributes to a deeper understanding of protein antigen and molecular analytes and presents analytical methods complementary to clinical evaluation for characterizing the performance of both laboratory-based and point-of-care rapid diagnostics for SARS-CoV-2.
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Wong ELY, Qiu H, Wang K, Sun KS, Yam CHK, Cheung AWL, Yeoh EK. Screening Hesitancy of a Universal Voluntary-based Rapid Antigen Test for coronavirus disease 2019 (COVID-19) During Omicron Wave in Hong Kong. J Infect Public Health 2023; 16:1306-1312. [PMID: 37336128 DOI: 10.1016/j.jiph.2023.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 06/02/2023] [Accepted: 06/07/2023] [Indexed: 06/21/2023] Open
Abstract
BACKGROUND The Hong Kong government distributed rapid antigen test (RAT) kits to households across the city and called for a universal voluntary testing exercise for three consecutive days during the Omicron wave to identify infected persons early for quarantine and disrupt transmission chains in the community. We conducted a survey to evaluate the participation rates and explore the determinants of voluntary RAT adoption and hesitancy. METHODS This cross-sectional survey was conducted through computer-assisted telephone interviews from 19 May to 16 June 2022 using an overlapping dual-frame telephone number sampling design. Information on willingness to adopt voluntary RAT, four themes of personal qualities, attitudes toward the government's health policies, incentives to motivate RAT adoption, and personal sociodemographic factors were collected. Logistic regression analysis was used to examine the factors associated with RAT adoption. RESULTS Of the 1010 participants, 490 successfully responded to the fixed-line and 520 to the mobile phone survey, with response rates of 1.42% and 1.63% and screen hesitancy rates of 36.1% and 39.3%, respectively. Participants of adoption RAT were those aged 30-49 years, with high perceived COVID-19 infection severity, ≥ 3 doses of COVID-19 vaccination, and more agreement with the health policies on material resources and quarantine orders. Individuals who were less risk seeking and more altruistic reported a higher adoption of voluntary RAT. CONCLUSIONS Understanding the willingness to participate in a voluntary universal testing programme might shed light on effective ways to minimise screening hesitancy in future public health strategies and campaigns.
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Affiliation(s)
- Eliza Lai-Yi Wong
- Centre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China.
| | - Hong Qiu
- Centre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Kailu Wang
- Centre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Kai-Sing Sun
- Centre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Carrie Ho-Kwan Yam
- Centre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Annie Wai-Ling Cheung
- Centre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Eng-Kiong Yeoh
- Centre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region of China
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