SARS-CoV-2 shedding dynamics across the respiratory tract, sex, and disease severity for adult and pediatric COVID-19

  1. Paul Z Chen
  2. Niklas Bobrovitz
  3. Zahra A Premji
  4. Marion Koopmans
  5. David N Fisman
  6. Frank X Gu

  • Curated by eLife

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    Evaluation Summary:

    The authors performed a systematic literature review and meta-analysis to develop a dataset of respiratory viral loads (rVLs) for SARS-CoV-2. Focus was on finding the relation between individual case characteristics (e.g. disease severity, age and sex) and lower and upper respiratory tract viral loads. The study appears robust and comprehensive, and the results are valuable and contribute to the scientific knowledge in this field.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)

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Abstract

Previously, we conducted a systematic review and analyzed the respiratory kinetics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (Chen et al., 2021). How age, sex, and coronavirus disease 2019 (COVID-19) severity interplay to influence the shedding dynamics of SARS-CoV-2, however, remains poorly understood.

Methods:

We updated our systematic dataset, collected individual case characteristics, and conducted stratified analyses of SARS-CoV-2 shedding dynamics in the upper (URT) and lower respiratory tract (LRT) across COVID-19 severity, sex, and age groups (aged 0–17 years, 18–59 years, and 60 years or older).

Results:

The systematic dataset included 1266 adults and 136 children with COVID-19. Our analyses indicated that high, persistent LRT shedding of SARS-CoV-2 characterized severe COVID-19 in adults. Severe cases tended to show slightly higher URT shedding post-symptom onset, but similar rates of viral clearance, when compared to nonsevere infections. After stratifying for disease severity, sex and age (including child vs. adult) were not predictive of respiratory shedding. The estimated accuracy for using LRT shedding as a prognostic indicator for COVID-19 severity was up to 81%, whereas it was up to 65% for URT shedding.

Conclusions:

Virological factors, especially in the LRT, facilitate the pathogenesis of severe COVID-19. Disease severity, rather than sex or age, predicts SARS-CoV-2 kinetics. LRT viral load may prognosticate COVID-19 severity in patients before the timing of deterioration and should do so more accurately than URT viral load.

Funding:

Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant, NSERC Senior Industrial Research Chair, and the Toronto COVID-19 Action Fund.

Article activity feed

  1. eLife

    Author Response:

    Reviewer #2 (Public Review):

    The study appears robust and comprehensive, and relevant quality checks for systematic review have been applied. The results are valuable and contribute to the scientific knowledge in this field.

    Interesting findings include:

    -Adult patients with severe disease had on average a somewhat higher upper respiratory tract viral load at 1 day from symptom onset than patients with non-severe disease. After this stratification for severity, respiratory viral loads did not differ significantly for age and sex. Rates of viral clearing were similar. Children and adults with non-severe disease had similar upper respiratory tract viral loads and viral clearance rates.

    -High and persistent lower respiratory tract shedding of SARS-CoV-2 was associated with severe but not non-severe illness. The difference in lower respiratory viral load for severe and non-severe cases was more pronounced than for upper respiratory tract viral loads. In contrast to the upper respiratory tract, viral clearance from the lower respiratory tract was more rapid in non-severe than in severe cases. Again, age and sex did not differ significantly after stratification for severity.

    -The authors then aimed to assess whether the observed difference in shedding in the first days after start of symptoms could be used to predict which people would develop more severe COVID-19. Typically, deterioration into severe disease only happens around 10 days from symptom onset. The authors conclude that upper respiratory tract viral shedding is so heterogeneous that its predictive capacity of disease severity is inaccurate. In contrast, lower respiratory tract shedding does have a predictive accuracy of up to 81% for disease severity.

    Potential impact: Lower respiratory tract viral load could thus potentially be used as an early warning for developing severe COVID-19. However, lower respiratory tract samples are not routinely taken, the standard nasopharyngeal swab is an upper respiratory sample. Some discussion on the practical applicability of this suggestion could enhance the paper's impact.

    We have included additional discussion on the applicability of this:

    “Thus, LRT shedding may predict COVID-19 severity, serving as a prognostic factor. As emerging evidence suggests that timing influences the efficacy of anti-SARS-CoV-2 therapies (O'Brien et al., 2021; D. M. Weinreich et al., 2021), early clinical decision making is crucial. A prognostic indicator guides early risk stratification, identifying high-risk individuals before they deteriorate into severe COVID-19. This facilitates the early administration of the efficacious therapies to these patients and may reduce the incidence of severe and fatal COVID-19 (O'Brien et al., 2021; D. M. Weinreich et al., 2021; David M. Weinreich et al., 2021). Additional studies should further explore the prognostic utility of LRT shedding in clinical settings, including towards improving COVID-19 outcomes.

    LRT shedding can be assessed noninvasively. This study predominantly analyzed expectorated sputum, which can be obtained from a deep cough, as the LRT specimen. Since SARS-CoV-2 detection occurs more frequently in expectorated sputum than in URT specimens, including nasopharyngeal swabs (Fajnzylber et al., 2020; Wang et al., 2020; Wolfel et al., 2020), SARS-CoV-2 quantitation from sputum may more accurately diagnose COVID-19 while simultaneously predicting severity. Noninvasively induced sputum presents a potential alternative for patients without sputum production (Lai et al., 2020), although it was not assessed in this study and its prognostic utility remains to be evaluated. Furthermore, our data suggest that sex and age may not significantly influence prognostic thresholds but that the time course of disease may. Prognostication should account for the dynamics of shedding, and both the rVL and DFSO of a sputum specimen should be considered.”

    (page 12-13, line 327-355).

  2. eLife

    Evaluation Summary:

    The authors performed a systematic literature review and meta-analysis to develop a dataset of respiratory viral loads (rVLs) for SARS-CoV-2. Focus was on finding the relation between individual case characteristics (e.g. disease severity, age and sex) and lower and upper respiratory tract viral loads. The study appears robust and comprehensive, and the results are valuable and contribute to the scientific knowledge in this field.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)

  3. eLife

    Reviewer #1 (Public Review):

    This manuscript presents a systematic review and regression analysis to analyze the association between upper and lower respiratory tract shedding (URT and LRT) of SARS-CoV-2 and disease severity. In addition, the authors study the impact of the days from symptoms onset on shedding in the two compartments. Overall, the presented results provide an interesting synthesis of the literature on these issues.

  4. eLife

    Reviewer #2 (Public Review):

    The study appears robust and comprehensive, and relevant quality checks for systematic review have been applied. The results are valuable and contribute to the scientific knowledge in this field.

    Interesting findings include:
    - Adult patients with severe disease had on average a somewhat higher upper respiratory tract viral load at 1 day from symptom onset than patients with non-severe disease. After this stratification for severity, respiratory viral loads did not differ significantly for age and sex. Rates of viral clearing were similar. Children and adults with non-severe disease had similar upper respiratory tract viral loads and viral clearance rates.

    - High and persistent lower respiratory tract shedding of SARS-CoV-2 was associated with severe but not non-severe illness. The difference in lower respiratory viral load for severe and non-severe cases was more pronounced than for upper respiratory tract viral loads. In contrast to the upper respiratory tract, viral clearance from the lower respiratory tract was more rapid in non-severe than in severe cases. Again, age and sex did not differ significantly after stratification for severity.

    - The authors then aimed to assess whether the observed difference in shedding in the first days after start of symptoms could be used to predict which people would develop more severe COVID-19. Typically, deterioration into severe disease only happens around 10 days from symptom onset. The authors conclude that upper respiratory tract viral shedding is so heterogeneous that its predictive capacity of disease severity is inaccurate. In contrast, lower respiratory tract shedding does have a predictive accuracy of up to 81% for disease severity.

    Potential impact: Lower respiratory tract viral load could thus potentially be used as an early warning for developing severe COVID-19. However, lower respiratory tract samples are not routinely taken, the standard nasopharyngeal swab is an upper respiratory sample. Some discussion on the practical applicability of this suggestion could enhance the paper's impact.

  5. Version published to 10.7554/elife.70458 on eLife
  6. Version published to 10.1101/2021.02.17.21251926v2 on medRxiv
  7. ScreenIT

    SciScore for 10.1101/2021.02.17.21251926: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data Sources and Searches: Up to 20 November 2020, we searched, without the use of filters or language restrictions, the following sources: MEDLINE (Ovid), EMBASE (Ovid), Cochrane Central Register of Controlled Trials (CENTRAL, Ovid), Web of Science Core Collection, and medRxiv and bioRxiv (both searched through Google Scholar via the Publish or Perish program).
    MEDLINE
    suggested: (MEDLINE, RRID:SCR_002185)
    EMBASE
    suggested: (EMBASE, RRID:SCR_001650)
    Cochrane Central Register of Controlled Trials
    suggested: (Cochrane Central Register of Controlled Trials, RRID:SCR_006576)
    bioRxiv
    suggested: (bioRxiv, RRID:SCR_003933)
    Google Scholar
    suggested: (Google Scholar, RRID:SCR_008878)
    Statistical analyses were performed using OriginPro 2019b (OriginLab) and the General Linear regression app or Matlab R2019b (MathWorks) and the Distribution Fitter app.
    OriginPro
    suggested: None
    Matlab
    suggested: (MATLAB, RRID:SCR_001622)

    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:
    Our study has limitations. First, while our study design systematically developed a large, diverse dataset, there were few severe female cases with LRT specimens and no severe pediatric cases included. Statistical comparisons involving these cohorts were not conducted based on increased sensitivity to sampling bias, as COVID-19 presents broad heterogeneity in rVL. Additional studies should permit these remaining comparisons. Second, our analyses did not assess the influence of therapies or additional case characteristics, including comorbidities. While the relationships between some comorbidities and SARS-CoV-2 kinetics remain unclear, recent studies indicate many potential therapies (e.g., remdesivir, hydroxychloroquine, lopinavir, ritonavir, low-dose monoclonal antibodies and ivermectin) have no significant anti-SARS-CoV-2 effects in patients (59-64). Third, the systematic dataset consisted largely of hospitalized patients, and our results may not generalize to asymptomatic infections. In summary, our findings provide insight into SARS-CoV-2 kinetics and describe virological factors that distinguish severe COVID-19 from nonsevere illness. They show that high, persistent LRT shedding characterizes severe disease in adults, highlighting the potential prognostic utility of SARS-CoV-2 quantitation from LRT specimens. Lastly, each study identified by our systematic review collected specimens before October 2020. As widespread transmission of the emerging variants of concern like...

    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.

  8. Version published to 10.1101/2021.02.17.21251926v1 on medRxiv