Mass Screening of Asymptomatic Persons for Severe Acute Respiratory Syndrome Coronavirus 2 Using Saliva

  1. Isao Yokota
  2. Peter Y Shane
  3. Kazufumi Okada
  4. Yoko Unoki
  5. Yichi Yang
  6. Tasuku Inao
  7. Kentaro Sakamaki
  8. Sumio Iwasaki
  9. Kasumi Hayasaka
  10. Junichi Sugita
  11. Mutsumi Nishida
  12. Shinichi Fujisawa
  13. Takanori Teshima

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Background

Coronavirus disease 2019 (COVID-19) has rapidly evolved to become a global pandemic, largely owing to the transmission of its causative virus through asymptomatic carriers. Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in asymptomatic people is an urgent priority for the prevention and containment of disease outbreaks in communities. However, few data are available in asymptomatic persons regarding the accuracy of polymerase chain reaction testing. In addition, although self-collected saliva samples have significant logistical advantages in mass screening, their utility as an alternative specimen in asymptomatic persons is yet to be determined.

Methods

We conducted a mass screening study to compare the utility of nucleic acid amplification, such as reverse-transcription polymerase chain reaction testing, using nasopharyngeal swab (NPS) and saliva samples from each individual in 2 cohorts of asymptomatic persons: the contact-tracing cohort and the airport quarantine cohort.

Results

In this mass screening study including 1924 individuals, the sensitivities of nucleic acid amplification testing with NPS and saliva specimens were 86% (90% credible interval, 77%–93%) and 92% (83%–97%), respectively, with specificities >99.9%. The true concordance probability between the NPS and saliva tests was estimated at 0.998 (90% credible interval, .996–.999) given the recent airport prevalence of 0.3%. In individuals testing positive, viral load was highly correlated between NPS and saliva specimens.

Conclusion

Both NPS and saliva specimens had high sensitivity and specificity. Self-collected saliva specimens are valuable for detecting SARS-CoV-2 in mass screening of asymptomatic persons.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.08.13.20174078: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was approved by the Institutional Ethics Board (Hokkaido University Hospital Division of Clinical Research Administration Number: 020-0116) and informed consent was obtained from all individuals.
    Consent: This study was approved by the Institutional Ethics Board (Hokkaido University Hospital Division of Clinical Research Administration Number: 020-0116) and informed consent was obtained from all individuals.
    Randomizationnot detected.
    Blindingnot detected.
    Power AnalysisSample size in the AQ cohort was calculated 1,818 based on the probability that 90% credible interval of specificity over 99.0% would be 0.8 (likes statistical power) under the expected specificity being 99.5%.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Among the limitations of any diagnostic modality is the possibility of obtaining false results with serious consequences. While persons infected with SARS-CoV-2 with falsely negative test may be left in society without the necessary precautions to keep him/her from transmitting the virus, false positive non-infected persons may undergo unnecessary quarantine and labour-intensive contact tracing measures. Although the high specificity of qRT-PCR reported herein may be reassuring in individual cases, the implications of mass testing depends on the prevalence of disease in the subject population. However, point prevalence is unknowable a priori and extremely difficult to assess in rapidly evolving outbreaks from carriers with relatively long presymptomatic periods. Rather, insights on mass testing may be gained through carefully monitoring test positivity in relation to the total number of tests performed. For example, with greater than 99.9% specificity, a positive result in five percent of all tests would indicate that more than 4.9% (out of the 5%) are true positives, with a positive predictive value (PPV) of at least 98%. On the other hand, if only 0.3% of all tests return positive (e.g. in isolated localities with very few disease), the PPV would be (0.3%-0.1%)/0.3% = 0.67, erroneously labelling one third of all positive tests. As PPV is dependent on the prevalence of disease, mass testing using a highly specific test will remain effective as long as test positivity remains...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1093/cid/ciaa1388
  3. ScreenIT

    SciScore for 10.1101/2020.08.13.20174078: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementThis study was approved by the Institutional Ethics Board (Hokkaido University Hospital Division of Clinical Research Administration Number: 020-0116) and informed consent was obtained from all individuals.Randomizationnot detected.Blindingnot detected.Power AnalysisSample size in the AQ cohort was calculated 1,818 based on the probability that 90% credible interval of specificity over 99.0% would be 0.8 (likes statistical power) under the expected specificity being 99.5%.Sex as a biological variableBackground characteristics contact-tracing cohort airport cohort N (%) N (%) Female 26 (16.1) 832 (47.2) Male 44 (27.3) 927 (52.6) unknown 91 (56.5) 4 (0.2) Median [IQR] 44.9

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

    Among the limitations of any diagnostic modality is the possibility of obtaining false results with serious consequences. While persons infected with SARS-CoV-2 with falsely negative test may be left in society without the necessary precautions to keep him/her from transmitting the virus, false positive non-infected persons may undergo unnecessary quarantine and labour-intensive contact tracing measures. Although the high specificity of qRT-PCR reported herein may be reassuring in individual cases, the implications of mass testing depends on the prevalence of disease in the subject population. However, point prevalence is unknowable a priori and extremely difficult to assess in rapidly evolving outbreaks from carriers with relatively long presymptomatic periods. Rather, insights on mass testing may be gained through carefully monitoring test positivity in relation to the total number of tests performed. For example, with greater than 99.9% specificity, a positive result in five percent of all tests would indicate that more than 4.9% (out of the 5%) are true positives, with a positive predictive value (PPV) of at least 98%. On the other hand, if only 0.3% of all tests return positive (e.g. in isolated localities with very few disease), the PPV would be (0.3%-0.1%)/0.3% = 0.67, erroneously labelling one third of all positive tests. As PPV is dependent on the prevalence of disease, mass testing using a highly specific test will remain effective as long as test positivity remains relatively high. RT-LAMP is an isothermal nucleic acid amplification technique that allows results to be obtained in approximately 30-60 minutes and a recent study showed the equivalent efficacy of RT-PCR and RT-LAMP in symptomatic patients [12]. In this study, we confirmed this in a large population of asymptomatic persons using saliva samples; there were no samples that were negative by NPS RT-LAMP and positive by saliva. It is unlikely that the sensitivity of the RT-LAMP method is significantly less than that of qRT-PCR, and the RT-LAMP testing has little impact on our conclusions. Our study suggests that RT-LAMP is a useful alternative to RT-PCR for the diagnosis of SARS-CoV-2. The current study lacks longitudinal data and clinical confirmation of positive cases. Nonetheless, this is the first study in asymptomatic individuals comparing paired samples of NPS and saliva. Rapid detection of asymptomatic infected patients is critical for the prevention of outbreaks of COVID-19 in communities and hospitals. Mass screening of the virus using self-collected saliva can be performed easily, non-invasively, and with minimal risk of viral transmission to health care workers. Contributors IY, KS, JS, MN and TT determined the study design. IY, PS, YU, SI, KH, MN, SF and TT collected the data. IY, KO, YU, YY, TI, KS did statistical analysis. IY, PS, TT drafted the manuscript and all authors reviewed critically and approved the final manuscript. Declaration of interests We declare no competing interests. Funding This study was funded by Health, Labour and Welfare Policy Research Grants 20HA2002. Acknowledgement We thank Tokyo international airport quarantine and Kansai international airport quarantine for cooperation; Megumi Aoki, Miwa Aoki, Nana Arai, Satomi Araki, Cao Cuicui, Kazumi Hasegawa, Masato Horiuchi, Dr. Nao Kurita, Dr. Aki Nakamura, Chiho Okabe, Mana Okamura, Yusuke Sakai, Dr. Akahito Sako, Natsumi Satake, Maki Shimatani, Kaki Tanaka, Maina Toguri, Sachiko Tominaga and Hana Wakasa for assistance in collecting saliva samples. Reference 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. Bohmer MM, Buchholz U, Corman VM, et al. Investigation of a COVID-19 outbreak in Germany resulting from a single travel-associated primary case: a case series. Lancet Infect Dis 2020. Bai Y, Yao L, Wei T, et al. Presumed asymptomatic carrier transmission of COVID-19. JAMA 2020. Moghadas SM, Fitzpatrick MC, Sah P, et al. The implications of silent transmission for the control of COVID-19 outbreaks. Proc Natl Acad Sci U S A 2020. Abbasi J. The promise and peril of antibody testing for COVID-19. JAMA 2020. Wang W, Xu Y, Gao R, et al. Detection of SARS-CoV-2 in different types of clinical specimens. JAMA 2020. Wang X, Tan L, Wang X, et al. Comparison of nasopharyngeal and oropharyngeal swabs for SARS-CoV-2 detection in 353 patients received tests with both specimens simultaneously. Int J Infect Dis 2020; 94: 107-9. To KK, Tsang OT, Chik-Yan Yip C, et al. Consistent detection of 2019 novel coronavirus in saliva. Clin Infect Dis 2020. Azzi L, Carcano G, Gianfagna F, et al. Saliva is a reliable tool to detect SARS-CoV-2. J Infect 2020. Williams E, Bond K, Zhang B, Putland M, Williamson DA. Saliva as a Noninvasive Specimen for Detection of SARS-CoV-2. J Clin Microbiol 2020; 58(8). Tu YP, Jennings R, Hart B, et al. Swabs collected by patients or health care workers for SARS-CoV-2 testing. N Engl J Med 2020. Iwasaki S, Fujisawa S, Nakakubo S, et al. Comparison of SARS-CoV-2 detection in nasopharyngeal swab and saliva. J Infect 2020. Nagura-Ikeda M, Imai K, Tabata S, et al. Clinical evaluation of self-collected saliva by RT-qPCR, direct RT-qPCR, RT-LAMP, and a rapid antigen test to diagnose COVID-19. J Clin Microbiol 2020. Notomi T, Okayama H, Masubuchi H, et al. Loop-mediated isothermal amplification of DNA. Nucleic Acids Res 2000; 28(12): E63. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. Park GS, Ku K, Baek SH, et al. Development of reverse transcription loop-mediated isothermal amplification assays targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). J Mol Diagn 2020; 22(6): 729-35. Joseph L, Gyorkos TW, Coupal L. Bayesian estimation of disease prevalence and the parameters of diagnostic tests in the absence of a gold standard. Am J Epidemiol 1995; 141(3): 263-72. Johnson WO, Gastwirth JL, Pearson LM. Screening without a "gold standard": the Hui-Walter paradigm revisited. Am J Epidemiol 2001; 153(9): 921-4. Wang C, Hanson TE. Estimation of sensitivity and specificity of multiple repeated binary tests without a gold standard. Stat Med 2019; 38(13): 2381-90. Woloshin S, Patel N, Kesselheim AS. False negative tests for SARS-CoV-2 infection - challenges and implications. N Engl J Med 2020. Zou L, Ruan F, Huang M, et al. SARS-CoV-2 viral load in upper respiratory specimens of infected patients. N Engl J Med 2020; 382(12): 1177-9. Fang Y, Zhang H, Xie J, et al. Sensitivity of chest CT for COVID-19: comparison to RT-PCR. Radiology 2020: 200432. Ai T, Yang Z, Hou H, et al. Correlation of chest CT and RT-PCR testing in coronavirus disease 2019 (COVID-19) in China: a report of 1014 cases. Radiology 2020: 200642. Guo L, Ren L, Yang S, et al. Profiling early humoral response to diagnose novel coronavirus disease (COVID-19). Clin Infect Dis 2020. Wyllie AL, Fournier J, Casanovas-Massana A, et al. Saliva is more sensitive for SARS-CoV-2 detectionin COVID-19 patients than nasopharyngeal swabs. medRxiv 2020. To KK, Tsang OT, Leung WS, et al. Temporal profiles of viral load in posterior oropharyngeal saliva samples and serum antibody responses during infection by SARS-CoV-2: an observational cohort study. Lancet Infect Dis 2020; 20(5): 565-74. Jamal MA, Mohammad M, Coomes E, et al. Sensitivity of nasopharyngeal swabs and saliva for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). medRxiv 2020. Becker D, Sandoval E, Amin A, al. e. Saliva is less sensitive than nasopharyngeal swabs for COVID-19 detection in the community setting. medRxiv 2020. He X, Lau EHY, Wu P, et al. Temporal dynamics in viral shedding and transmissibility of COVID-19. Nat Med 2020; 26(5): 672-5. 28. 29. 30. Arons MM, Hatfield KM, Reddy SC, et al. Presymptomatic SARS-CoV-2 infections and transmission in a skilled nursing facility. N Engl J Med 2020; 382(22): 2081-90. La Scola B, Le Bideau M, Andreani J, et al. Viral RNA load as determined by cell culture as a management tool for discharge of SARS-CoV-2 patients from infectious disease wards. Eur J Clin Microbiol Infect Dis 2020; 39(6): 1059-61. Bullard J, Dust K, Funk D, et al. Predicting infectious SARS-CoV-2 from diagnostic samples. Clin Infect Dis 2020. Table 1. Background characteristics contact-tracing cohort airport cohort N (%) N (%) Female 26 (16.1) 832 (47.2) Male 44 (27.3) 927 (52.6) unknown 91 (56.5) 4 (0.2) Median [IQR] 44.9 [29.8, 66.4] 33.5 [22.6, 47.4] -19 2 (1.2) 299 (17.0) 20-29 16 (9.9) 433 (24.6) 30-39 13 (8.1) 344 (19.5) 40-49 9 (5.6) 324 (18.4) 50-59 8 (5.0) 230 (13.0) 60-69 9 (5.6) 97 (5.5) 70- 13 (8.1) 34 (1.9) unknown 91 (56.5) 2 (0.1) North America - 713 (40.4) Asia and Oceania - 583 (33.1) Europe - 467 (26.5) Sex Age Last point of embarkation Table 2. Diagnostic results of nasopharyngeal swab (NPS) and saliva test (a) Contact-tracing cohort (n=161) saliva NPS positive negative positive negative 38 6 3 114 (b) Airport Quarantine cohort (n=1,763) saliva NPS positive negative positive negative 4 0 1 1758 Figure 1. Flow diagram of participants Figure 2. The sensitivity and specificity of nasopharyngeal swab and saliva Histograms of posterior distribution of (a) sensitivity and (b) specificity. Point estimates and 90% credible interval (90%CI) defined by 5th to 95th percentile are shown. Figure 3. True concordance probability with varying rates of prevalence. The true concordance probability of diagnosis between nasopharyngeal swab and saliva test in populations with various prevalence. Solid line indicates point estimates and dashed lines indicate 90% credible interval. Figure 4. Comparison of the viral load between NPS and saliva (a) Ct values determined with the qRT-PCR test of nasopharyngeal swab and saliva are plotted. (b) Times to detecting positive results (Tp) determined by the RT-LAMP test of saliva are plotted against Ct values determined by the qRT-PCR test of saliva. W indicates Kendall’s coefficient of concordance. Data were plotted with one of the tests being positive and the values being measured. Supplement 1. True concordance probability under several scenarios. gure 1 Contact-Tracing (CT) cohort 288 persons screened Airport Q 2,270 per Declined to participate (n=30) Symptomatic persons (n=95) Insufficient saliva volume (n=2) 161 persons were analyzed 1,763 perso (a) sensitivity 0 0 2 2 4 4 6 6 8 8 10 86% (90%CI: 77-93%) 10 NPS 50 60 70 80 90 100 % 50 (b) specificity 600 600 1200 1800 99.93% (90%CI: 99.77-99.99%) 1200 1800 NPS 0 0 Figure 2 99.0 99.2 99.4 99.6 99.8 100.0 % 99.0 0.0 0.2 0.4 0.6 0.8 True concordance probability 1.0 gure 3 0 10 20 Prevalence gure 4 qRT-PCR between NPS and saliva (n=45) (b) qRT-PC und 30 10 20 Tp [min] 30 20 10 0 Kendall’s W =0.87 0 Ct value in saliva 40 40 undetermined 0 10 20 30 Ct value in nasopharyngeal swabs 40 undetermined 0

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  4. Version published to 10.1101/2020.08.13.20174078v2 on medRxiv
  5. Version published to 10.1101/2020.08.13.20174078v1 on medRxiv