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Comparison of Rapid Antigen Tests' Performance Between Delta and Omicron Variants of SARS-CoV-2 : A Secondary Analysis From a Serial Home Self-testing Study.
Soni, Apurv; Herbert, Carly; Filippaios, Andreas; Broach, John; Colubri, Andres; Fahey, Nisha; Woods, Kelsey; Nanavati, Janvi; Wright, Colton; Orwig, Taylor; Gilliam, Karen; Kheterpal, Vik; Suvarna, Thejas; Nowak, Chris; Schrader, Summer; Lin, Honghuang; O'Connor, Laurel; Pretz, Caitlin; Ayturk, Didem; Orvek, Elizabeth; Flahive, Julie; Lazar, Peter; Shi, Qiming; Achenbach, Chad; Murphy, Robert; Robinson, Matthew; Gibson, Laura; Stamegna, Pamela; Hafer, Nathaniel; Luzuriaga, Katherine; Barton, Bruce; Heetderks, William; Manabe, Yukari C; McManus, David.
  • Soni A; Program in Digital Medicine and Division of Clinical Informatics, Department of Medicine, and Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (A.S.).
  • Herbert C; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.).
  • Filippaios A; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.).
  • Broach J; Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (J.B., L.O.).
  • Colubri A; Department of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School, Worcester, Massachusetts (A.C.).
  • Fahey N; Program in Digital Medicine, Department of Medicine, Department of Population and Quantitative Health Sciences, and Department of Pediatrics, University of Massachusetts Chan Medical School, Worcester, Massachusetts (N.F.).
  • Woods K; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.).
  • Nanavati J; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.).
  • Wright C; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.).
  • Orwig T; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.).
  • Gilliam K; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.).
  • Kheterpal V; CareEvolution, Ann Arbor, Michigan (V.K., T.S., C.N., S.S.).
  • Suvarna T; CareEvolution, Ann Arbor, Michigan (V.K., T.S., C.N., S.S.).
  • Nowak C; CareEvolution, Ann Arbor, Michigan (V.K., T.S., C.N., S.S.).
  • Schrader S; CareEvolution, Ann Arbor, Michigan (V.K., T.S., C.N., S.S.).
  • Lin H; Program in Digital Medicine and Division of Clinical Informatics, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (H.L.).
  • O'Connor L; Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (J.B., L.O.).
  • Pretz C; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.).
  • Ayturk D; Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.A., E.O., J.F., P.L., B.B.).
  • Orvek E; Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.A., E.O., J.F., P.L., B.B.).
  • Flahive J; Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.A., E.O., J.F., P.L., B.B.).
  • Lazar P; Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.A., E.O., J.F., P.L., B.B.).
  • Shi Q; Program in Digital Medicine, Department of Medicine, Department of Population and Quantitative Health Sciences, and University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, Massachusetts (Q.S.).
  • Achenbach C; Division of Infectious Disease, Department of Medicine, Havey Institute for Global Health, Feinberg School of Medicine, Northwestern University, Chicago, Illinois (C.A., R.M.).
  • Murphy R; Division of Infectious Disease, Department of Medicine, Havey Institute for Global Health, Feinberg School of Medicine, Northwestern University, Chicago, Illinois (C.A., R.M.).
  • Robinson M; Division of Infectious Disease, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland (M.R., Y.C.M.).
  • Gibson L; Department of Pediatrics and Division of Infectious Disease, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (L.G.).
  • Stamegna P; University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, Massachusetts (P.S., N.H.).
  • Hafer N; University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, Massachusetts (P.S., N.H.).
  • Luzuriaga K; University of Massachusetts Center for Clinical and Translational Science and Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (K.L.).
  • Barton B; Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.A., E.O., J.F., P.L., B.B.).
  • Heetderks W; National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland (W.H.).
  • Manabe YC; Division of Infectious Disease, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland (M.R., Y.C.M.).
  • McManus D; Program in Digital Medicine and Division of Cardiology, Department of Medicine, and Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.M.).
Ann Intern Med ; 2022 Oct 11.
Article in English | MEDLINE | ID: covidwho-2203114
ABSTRACT

BACKGROUND:

It is important to document the performance of rapid antigen tests (Ag-RDTs) in detecting SARS-CoV-2 variants.

OBJECTIVE:

To compare the performance of Ag-RDTs in detecting the Delta (B.1.617.2) and Omicron (B.1.1.529) variants of SARS-CoV-2.

DESIGN:

Secondary analysis of a prospective cohort study that enrolled participants between 18 October 2021 and 24 January 2022. Participants did Ag-RDTs and collected samples for reverse transcriptase polymerase chain reaction (RT-PCR) testing every 48 hours for 15 days.

SETTING:

The parent study enrolled participants throughout the mainland United States through a digital platform. All participants self-collected anterior nasal swabs for rapid antigen testing and RT-PCR testing. All Ag-RDTs were completed at home, whereas nasal swabs for RT-PCR were shipped to a central laboratory.

PARTICIPANTS:

Of 7349 participants enrolled in the parent study, 5779 asymptomatic persons who tested negative for SARS-CoV-2 on day 1 of the study were eligible for this substudy. MEASUREMENTS Sensitivity of Ag-RDTs on the same day as the first positive (index) RT-PCR result and 48 hours after the first positive RT-PCR result.

RESULTS:

A total of 207 participants were positive on RT-PCR (58 Delta, 149 Omicron). Differences in sensitivity between variants were not statistically significant (same day Delta, 15.5% [95% CI, 6.2% to 24.8%] vs. Omicron, 22.1% [CI, 15.5% to 28.8%]; at 48 hours Delta, 44.8% [CI, 32.0% to 57.6%] vs. Omicron, 49.7% [CI, 41.6% to 57.6%]). Among 109 participants who had RT-PCR-positive results for 48 hours, rapid antigen sensitivity did not differ significantly between Delta- and Omicron-infected participants (48-hour sensitivity Delta, 81.5% [CI, 66.8% to 96.1%] vs. Omicron, 78.0% [CI, 69.1% to 87.0%]). Only 7.2% of the 69 participants with RT-PCR-positive results for shorter than 48 hours tested positive by Ag-RDT within 1 week; those with Delta infections remained consistently negative on Ag-RDTs.

LIMITATION:

A testing frequency of 48 hours does not allow a finer temporal resolution of the analysis of test performance, and the results of Ag-RDTs are based on self-report.

CONCLUSION:

The performance of Ag-RDTs in persons infected with the SARS-CoV-2 Omicron variant is not inferior to that in persons with Delta infections. Serial testing improved the sensitivity of Ag-RDTs for both variants. The performance of rapid antigen testing varies on the basis of duration of RT-PCR positivity. PRIMARY FUNDING SOURCE National Heart, Lung, and Blood Institute of the National Institutes of Health.

Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Diagnostic study / Observational study / Prognostic study Topics: Variants Language: English Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Diagnostic study / Observational study / Prognostic study Topics: Variants Language: English Year: 2022 Document Type: Article