Viral dynamics of acute SARS-CoV-2 infection and applications to diagnostic and public health strategies

  1. Stephen M. Kissler
  2. Joseph R. Fauver
  3. Christina Mack
  4. Scott W. Olesen
  5. Caroline Tai
  6. Kristin Y. Shiue
  7. Chaney C. Kalinich
  8. Sarah Jednak
  9. Isabel M. Ott
  10. Chantal B. F. Vogels
  11. Jay Wohlgemuth
  12. James Weisberger
  13. John DiFiori
  14. Deverick J. Anderson
  15. Jimmie Mancell
  16. David D. Ho
  17. Nathan D. Grubaugh
  18. Yonatan H. Grad

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

SARS-CoV-2 infections are characterized by viral proliferation and clearance phases and can be followed by low-level persistent viral RNA shedding. The dynamics of viral RNA concentration, particularly in the early stages of infection, can inform clinical measures and interventions such as test-based screening. We used prospective longitudinal quantitative reverse transcription PCR testing to measure the viral RNA trajectories for 68 individuals during the resumption of the 2019–2020 National Basketball Association season. For 46 individuals with acute infections, we inferred the peak viral concentration and the duration of the viral proliferation and clearance phases. According to our mathematical model, we found that viral RNA concentrations peaked an average of 3.3 days (95% credible interval [CI] 2.5, 4.2) after first possible detectability at a cycle threshold value of 22.3 (95% CI 20.5, 23.9). The viral clearance phase lasted longer for symptomatic individuals (10.9 days [95% CI 7.9, 14.4]) than for asymptomatic individuals (7.8 days [95% CI 6.1, 9.7]). A second test within 2 days after an initial positive PCR test substantially improves certainty about a patient’s infection stage. The effective sensitivity of a test intended to identify infectious individuals declines substantially with test turnaround time. These findings indicate that SARS-CoV-2 viral concentrations peak rapidly regardless of symptoms. Sequential tests can help reveal a patient’s progress through infection stages. Frequent, rapid-turnaround testing is needed to effectively screen individuals before they become infectious.

Article activity feed

  1. Version published to 10.1371/journal.pbio.3001333
  2. Version published to 10.1101/2020.10.21.20217042v3 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2020.10.21.20217042: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Residual viral transport media (VTM) from Quest Diagnostics or BioReference Laboratories were shipped overnight to Yale on dry ice.
    Quest
    suggested: (QUEST, RRID:SCR_005210)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.

  4. Version published to 10.1101/2020.10.21.20217042v2 on medRxiv
  5. ScreenIT

    SciScore for 10.1101/2020.10.21.20217042: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The samples were initially tested by either Quest Diagnostics (while teams were in local markets using the Quest SARS-CoV-2 RT-qPCR (7)) or BioReference Laboratories (while teams were in Orlando using the cobas SARS-CoV-2 test (8)).
    Quest
    suggested: (QUEST, RRID:SCR_005210)

    Results from OddPub: Thank you for sharing your code.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.

    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.

  6. Version published to 10.1101/2020.10.21.20217042v1 on medRxiv