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Figure.  Longitudinal Analysis of SARS-CoV-2 Nucleocapsid and Viral Genome Levels
Longitudinal Analysis of SARS-CoV-2 Nucleocapsid and Viral Genome Levels

Graphs show longitudinal analysis of SARS-CoV-2 nucleocapsid and viral genome levels using an at-home, semiquantitative direct antigen rapid test (DART) and quantitative real-time polymerase chain reaction (qRT-PCR) for 15 positive participants. The orange lines represent the DART data for each individual, the dark blue lines represent the viral RNA target N1, and the light blue lines represents the viral target N2. The x-axis corresponds to number of days after first reported symptoms, with 0 indicating 1 day before symptoms onset. The left y-axis corresponds to background subtracted DART signal normalized to the control line for each test. The right y-axis corresponds to the cycle threshold of viral RNA targets N1 and N2 in each sample. DART results less than 10% of control are considered negative results, which is indicated by the orange dashed line.

Table.  Sensitivity Data
Sensitivity Data
1.
Zhou  P, Yang  XL, Wang  XG,  et al.  A pneumonia outbreak associated with a new coronavirus of probable bat origin.   Nature. 2020;579(7798):270-273. doi:10.1038/s41586-020-2012-7PubMedGoogle ScholarCrossref
2.
World Health Organization. WHO coronavirus (COVID-19) dashboard. Accessed August 2, 2021. https://covid19.who.int/
3.
Ashcroft  P, Lehtinen  S, Angst  DC, Low  N, Bonhoeffer  S.  Quantifying the impact of quarantine duration on COVID-19 transmission.   eLife. 2021;10:e63704. doi:10.7554/eLife.63704PubMedGoogle Scholar
4.
Lu  X, Wang  L, Sakthivel  SK,  et al.  US CDC real-time reverse transcription PCR panel for detection of severe acute respiratory syndrome coronavirus 2.   Emerg Infect Dis. 2020;26(8). doi:10.3201/eid2608.201246PubMedGoogle Scholar
5.
Bosch  I, de Puig  H, Hiley  M,  et al.  Rapid antigen tests for dengue virus serotypes and Zika virus in patient serum.   Sci Transl Med. 2017;9(409):eaan1589. doi:10.1126/scitranslmed.aan1589PubMedGoogle Scholar
6.
Larremore  DB, Wilder  B, Lester  E,  et al.  Test sensitivity is secondary to frequency and turnaround time for COVID-19 screening.   Sci Adv. 2021;7(1):eabd5393. doi:10.1126/sciadv.abd5393PubMedGoogle Scholar
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    Research Letter
    Infectious Diseases
    August 27, 2021

    Validation of an At-Home Direct Antigen Rapid Test for COVID-19

    Author Affiliations
    • 1E25Bio, Inc, Cambridge, Massachusetts
    • 2LabCentral, Inc, Cambridge, Massachusetts
    • 3Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
    • 4Department of Medicine, Mount Sinai School of Medicine, New York, New York
    • 5BioLabs (BioInnovation Labs, LLC), Cambridge, Massachusetts
    JAMA Netw Open. 2021;4(8):e2126931. doi:10.1001/jamanetworkopen.2021.26931
    Introduction

    Since its discovery, the SARS-CoV-2 virus has created a global pandemic of COVID-19.1 As of August 2, 2021, more than 198 million infections were reported worldwide.2 Typical symptoms include fatigue, fever, cough, and anosmia or dysgeusia.

    Outbreak management has been hindered by high transmission rates and limitations in testing capacity. Effective public health tools are needed for rapid and early detection. The current diagnostic standard is quantitative real-time polymerase chain reaction (qRT-PCR), but its cost and long turnaround times limit its utility for widespread surveillance. Lack of surveillance has caused severe societal disruption.

    Rapid antigen tests that permit new cases to isolate immediately can be important surveillance tools.3 A longitudinal comparison between antigen tests performed at home and qRT-PCR has not previously been performed, to our knowledge. Here, we describe implementation of high-frequency testing using inexpensive, at-home, semiquantitative, direct antigen rapid tests (DARTs) and compare their performance with that of qRT-PCR on self-collected nasal specimens.

    Methods

    This cohort study follows the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for observational studies and was conducted after review and approval by the Advarra institutional review board. Participants provided written informed consent signed electronically.

    The study included 257 affiliates of 3 coworking laboratories in Cambridge and Boston, Massachusetts. The prevalence of COVID-19 in this area during the study was between less than 1% and 8%. Individuals self-collected nasal swab specimens twice weekly at home during a 6-month period. DART was performed at home, and the findings were compared with laboratory qRT-PCR tests.4,5 Symptom information was collected contemporaneously. Self-reported race and ethnicity were collected in accordance with Department of Health and Human Services and Food and Drug Administration reporting guidelines for non–laboratory-based tests.

    The 95% CIs for sensitivity and specificity were calculated using generalized estimating equations in Rstudio version 4.1.0 (R Project for Statistical Computing) with a working independence correlation structure accounting for clusters of multiple tests per individual. The 2-sided binomial Clopper-Pearson method was used to calculate 95% CIs for day-by-day sensitivity for days 0 to 7 of symptoms, when there was a maximum of 1 test per individual. See the eAppendix and the eFigure in the Supplement for additional details.

    Results

    A total of 257 participants were enrolled (median age, 35 years; range, 21-72 years). Among the participants, 120 (46.7%) were women, 161 (62.6%) were White, 49 (19.1%) were Asian, 29 (11.3%) were Hispanic, and 8 (3.1%) were Black. A total of 2951 pairs of nasal swabs were self-collected by participants and tested by qRT-PCR and DART. The sensitivity of DART within days 0 to 12 of symptom onset was 78.9% (60 of 76 swabs; 95% CI, 69.1%-88.8%), and the specificity of DART was 97.1% (2791 of 2875 swabs; 95% CI, 96.3%-97.8%) (Table).

    The duration of SARS-CoV-2 nucleocapsid and RNA detection for individual infections ranged from 1 to 12 days, with peak levels observed between 2 and 6 days of symptoms (median, 3 days). The sensitivity of DART was calculated for each day. DART sensitivity was 96.2% (25 of 26 swabs; 95% CI, 88.8%-100.0%) within days 0 to 3 of symptoms (Table).

    Of the 257 individuals, 15 contracted COVID-19. Twice-weekly DART detected 15 of 15 of infections (100%). The Figure shows the performance of DART compared with qRT-PCR. Results were plotted relative to days after symptoms onset. Eleven participants tested positive on day 1 or 2. One was presymptomatic the day of their initial DART positive result. One infection was detected by qRT-PCR 1 day before DART. For 1 positive participant, DART detected infection 1 day before qRT-PCR did.

    Discussion

    We sought to validate the effectiveness of DART and to test whether at-home testing with DART could prevent the spread of SARS-CoV-2 in a coworking environment. In this cohort study of 257 individuals who collected 2951 sample pairs over the course of 6 months, we found that twice-weekly surveillance with DART detected infections in 15 individuals, with 96.2% sensitivity on days 0 through 3 of symptoms. Detection on day 3 is almost as effective as detection on day 1 for reducing the incidence of COVID-19, if 75% of a population is surveilled.6 The prevalence of disease dictates the frequency of testing and its effectiveness for controlling potential outbreaks. Limitations of this study include low infection rates among the study population. During this study, the prevalence of COVID-19 was between less than 1% and 8%.

    Use of twice-weekly DART testing allowed the activities of the coworking sites to continue safely during the pandemic. Most of the positive participants reported that they did not recognize symptoms of COVID-19 until they received a positive result. Policies that rely on self-reported symptoms miss or delay detection and allow viral spread within communities. Frequent at-home testing with DART allows infected individuals to be identified and quarantined immediately. Such surveillance can prevent viral transmission in in-person work environments or other social settings.

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    Article Information

    Accepted for Publication: July 26, 2021.

    Published: August 27, 2021. doi:10.1001/jamanetworkopen.2021.26931

    Correction: This article was corrected on October 1, 2021, to fix errors in the Results, Discussion, and Table.

    Open Access: This is an open access article distributed under the terms of the CC-BY-NC-ND License. © 2021 Harmon A et al. JAMA Network Open.

    Corresponding Author: Laura E. Holberger, PhD, BioLabs (BioInnovation Labs, LLC), 139 Main St, 4th Floor, Cambridge, MA 01239 (laura@biolabs.io).

    Author Contributions: Drs Holberger and Bosch had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Mr Harmon and Ms Chang contributed equally as co–first authors.

    Concept and design: Harmon, Chang, Sena, Herrera, Bosch, Holberger.

    Acquisition, analysis, or interpretation of data: All authors.

    Drafting of the manuscript: Salcedo, Sena, Herrera, Bosch, Holberger.

    Critical revision of the manuscript for important intellectual content: All authors.

    Statistical analysis: Harmon, Salcedo, Herrera, Bosch, Holberger.

    Obtained funding: Chang, Bosch, Holberger.

    Administrative, technical, or material support: Chang, Sena, Bosch, Holberger.

    Supervision: Chang, Sena, Herrera, Bosch, Holberger.

    Conflict of Interest Disclosures: Ms Salcedo, Ms Sena, and Dr Herrera are employed by and have a financial interest in E25Bio, Inc, a biotechnology company that develops rapid tests for infectious diseases. At the time of the study, Mr Harmon and Dr Bosch were employed by E25Bio, Inc, and have a financial interest in the company. No other disclosures were reported.

    Funding/Support: Funding was provided by E25Bio, Inc, LabCentral, Inc, and BioLabs, LLC, in 3 equal parts.

    Role of the Funder/Sponsor: The 3 funding entities formed the Cambridge Consortium for Rapid COVID-19 Tests and were each involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

    Additional Contributions: We thank all the participants in the study. Elena Naumova, PhD (Tufts University), assisted with the statistical analysis for this manuscript. Nikhil Lal, MEng (E25Bio, Inc), developed the digital platform. Adam R. Gomez, MS (E25Bio, Inc), and Dimitris P. Papageorgiou, PhD (E25Bio, Inc), assisted with data collection. Johannes Fruehauf, MD, PhD (BioLabs, LLC, and LabCentral, Inc), Sina Hoche, MA (Harvard University), and Prerna Sekhri, MS (LabCentral, Inc), assisted with study design. Sally Aubrey, BA (LabCentral, Inc), assisted with study execution. None of these individuals was compensated beyond their normal salaries.

    Additional Information: LabCentral, Inc, donated operational support, laboratory space, and equipment for this work. BioLabs, LLC, and E25Bio, Inc, donated oversight and scientist time. Integra Biosciences, Scismic, and BioIT each contributed equipment or services.

    References
    1.
    Zhou  P, Yang  XL, Wang  XG,  et al.  A pneumonia outbreak associated with a new coronavirus of probable bat origin.   Nature. 2020;579(7798):270-273. doi:10.1038/s41586-020-2012-7PubMedGoogle ScholarCrossref
    2.
    World Health Organization. WHO coronavirus (COVID-19) dashboard. Accessed August 2, 2021. https://covid19.who.int/
    3.
    Ashcroft  P, Lehtinen  S, Angst  DC, Low  N, Bonhoeffer  S.  Quantifying the impact of quarantine duration on COVID-19 transmission.   eLife. 2021;10:e63704. doi:10.7554/eLife.63704PubMedGoogle Scholar
    4.
    Lu  X, Wang  L, Sakthivel  SK,  et al.  US CDC real-time reverse transcription PCR panel for detection of severe acute respiratory syndrome coronavirus 2.   Emerg Infect Dis. 2020;26(8). doi:10.3201/eid2608.201246PubMedGoogle Scholar
    5.
    Bosch  I, de Puig  H, Hiley  M,  et al.  Rapid antigen tests for dengue virus serotypes and Zika virus in patient serum.   Sci Transl Med. 2017;9(409):eaan1589. doi:10.1126/scitranslmed.aan1589PubMedGoogle Scholar
    6.
    Larremore  DB, Wilder  B, Lester  E,  et al.  Test sensitivity is secondary to frequency and turnaround time for COVID-19 screening.   Sci Adv. 2021;7(1):eabd5393. doi:10.1126/sciadv.abd5393PubMedGoogle Scholar
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