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Saliva or Nasopharyngeal Swab Specimens for Detection of SARS-CoV-2

Open access
Wyllie, Anne L., Fournier, John, Casanovas-Massana, Arnau, Campbell, Melissa, Tokuyama, Maria, Vijayakumar, Pavithra, Warren, Joshua L., Geng, Bertie, Muenker, M. Catherine, Moore, Adam J., Vogels, Chantal B.F., Petrone, Mary E., Ott, Isabel M., Lu, Peiwen, Venkataraman, Arvind, Lu-Culligan, Alice, Klein, Jonathan, Earnest, Rebecca, Simonov, Michael, Datta, Rupak, Handoko, Ryan, Naushad, Nida, Sewanan, Lorenzo R., Valdez, Jordan, White, Elizabeth B., Lapidus, Sarah, Kalinich, Chaney C., Jiang, Xiaodong, Kim, Daniel J., Kudo, Eriko, Linehan, Melissa, Mao, Tianyang, Moriyama, Miyu, Oh, Ji E., Park, Annsea, Silva, Julio, Song, Eric, Takahashi, Takehiro, Taura, Manabu, Weizman, Orr-El, Wong, Patrick, Yang, Yexin, Bermejo, Santos, Odio, Camila D., Omer, Saad B., Dela Cruz, Charles S., Farhadian, Shelli, Martinello, Richard A., Iwasaki, Akiko, Grubaugh, Nathan D., Ko, Albert I.·2020·New England Journal of Medicine

Abstract

Abstract Rapid and accurate SARS-CoV-2 diagnostic testing is essential for controlling the ongoing COVID-19 pandemic. The current gold standard for COVID-19 diagnosis is real-time RT-PCR detection of SARS-CoV-2 from nasopharyngeal swabs. Low sensitivity, exposure risks to healthcare workers, and global shortages of swabs and personal protective equipment, however, necessitate the validation of new diagnostic approaches. Saliva is a promising candidate for SARS-CoV-2 diagnostics because (1) collection is minimally invasive and can reliably be self-administered and (2) saliva has exhibited comparable sensitivity to nasopharyngeal swabs in detection of other respiratory pathogens, including endemic human coronaviruses, in previous studies. To validate the use of saliva for SARS-CoV-2 detection, we tested nasopharyngeal and saliva samples from confirmed COVID-19 patients and self-collected samples from healthcare workers on COVID-19 wards. When we compared SARS-CoV-2 detection from patient-matched nasopharyngeal and saliva samples, we found that saliva yielded greater detection sensitivity and consistency throughout the course of infection. Furthermore, we report less variability in self-sample collection of saliva. Taken together, our findings demonstrate that saliva is a viable and more sensitive alternative to nasopharyngeal swabs and could enable at-home self-administered sample collection for accurate large-scale SARS-CoV-2 testing.

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Metadata

Authors
Wyllie, A. L., Fournier, J., Casanovas-Massana, A., Campbell, M., Tokuyama, M., Vijayakumar, P., Warren, J. L., Geng, B., Muenker, M. C., Moore, A. J., Vogels, C. B. F., Petrone, M. E., Ott, I. M., Lu, P., Venkataraman, A., Lu-Culligan, A., Klein, J., Earnest, R., Simonov, M., Datta, R., Handoko, R., Naushad, N., Sewanan, L. R., Valdez, J., White, E. B., Lapidus, S., Kalinich, C. C., Jiang, X., Kim, D. J., Kudo, E., Linehan, M., Mao, T., Moriyama, M., Oh, J. E., Park, A., Silva, J., Song, E., Takahashi, T., Taura, M., Weizman, O.-E., Wong, P., Yang, Y., Bermejo, S., Odio, C. D., Omer, S. B., Dela Cruz, C. S., Farhadian, S., Martinello, R. A., Iwasaki, A., Grubaugh, N. D., & Ko, A. I.
Venue
New England Journal of Medicine
Published
2020-09-24
Volume
383
Issue
13
Pages
1283-1286
ISSN
  • 0028-4793 (ISSN-L)
  • 1533-4406
OpenAlex
W3080652759
Cited by
1,169
References
4
FWCI
31.42
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Saliva or Nasopharyngeal Swab Specimens for Detection of SARS-CoV-2. https://app.cochat.ai/papers/10.1056/nejmc2016359
The paper
Wyllie, A. L., Fournier, J., Casanovas-Massana, A., Campbell, M., Tokuyama, M., Vijayakumar, P., Warren, J. L., Geng, B., Muenker, M. C., Moore, A. J., Vogels, C. B. F., Petrone, M. E., Ott, I. M., Lu, P., Venkataraman, A., Lu-Culligan, A., Klein, J., Earnest, R., Simonov, M., . . . Ko, A. I. (2020). Saliva or Nasopharyngeal Swab Specimens for Detection of SARS-CoV-2. New England Journal of Medicine. https://doi.org/10.1056/nejmc2016359

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.