SARS-CoV-2 RNA shedding in recovered COVID-19 cases and the presence of antibodies against SARS-CoV-2 in recovered COVID-19 cases and close contacts

  1. Chintana Chirathaworn
  2. Manit Sripramote
  3. Piti Chalongviriyalert
  4. Supunee Jirajariyavej
  5. Phatharaporn Kiatpanabhikul
  6. Jatuporn Saiyarin
  7. Chulikorn Soudon
  8. Orawan Thienfaidee
  9. Thitisan Palakawong Na Ayuthaya
  10. Chantapat Brukesawan
  11. Dootchai Chaiwanichsiri
  12. Duangnapa Intharasongkroh
  13. Nasamon Wanlapakorn
  14. Jira Chansaenroj
  15. Jiratchaya Puenpa
  16. Ritthideach Yorsaeng
  17. Arunee Thitithanyanont
  18. Rungrueng Kitphati
  19. Anek Mungaomklang
  20. Pijaya Nagavajara
  21. Yong Poovorawan

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Abstract

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 emerged in December 2019 and has spread globally. Although Thailand has been effective at controlling the spread of COVID-19, disease surveillance and information on antibody responses in infected cases and close contacts are needed because there is still no specific treatment or vaccine available. We investigated 217 recovered COVID-19 cases to monitor their viral RNA shedding and production of antibodies against SARS-CoV-2. The presence of antibodies in blood samples from 308 close contacts of COVID-19 cases was also determined. Viral RNA was still detectable in 6.6 % of recovered COVID-19 cases. The most prolonged duration of viral RNA shedding detected in this study was 105 days. IgM, IgG, and IgA antibodies against SARS-CoV-2 were detected in 13.82, 88.48, and 83.41 % of the recovered cases 4–12 weeks after disease onset, respectively. Although the patients had recovered from their illness, the levels of antibodies detected showed association with their symptoms during their stay in hospital. Fifteen of the 308 contacts (4.87 %) of COVID-19 cases tested positive for IgG antibodies. The presence of antibodies against SARS-CoV-2 suggested that there was viral exposure among close contacts. Viral clearance and the pattern of antibody responses in infected individuals are both crucial for effectively combatting SARS-CoV-2. Our study provides additional information on the natural history of this newly emerging disease related to both natural host defenses and a strategy for vaccine development.

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  1. ScreenIT

    SciScore for 10.1101/2020.07.17.208439: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIACUC: The study protocol was approved by the Institutional Ethics Committee (IRB) of the Bangkok Metropolitan Administration, Thailand (IRB No. M001h/63_Exp).
    Consent: The IRB waived the need for consent because the used samples were obtained from routine preventive measures and were de-identified and anonymous.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Detection of antibodies against SARS-CoV-2 by enzyme-linked immunoassays: For recovered COVID-19 cases, IgM, IgG, and IgA antibodies against SARS-CoV-2 were determined, whereas, for close contacts, IgG antibodies were investigated in blood samples.
    IgM, IgG
    suggested: None
    SARS-CoV-2
    suggested: None
    IgG
    suggested: None
    The determination of IgG and IgA antibodies was performed using an ELISA automated system (Euroimmun, Luebeck, Germany) following the manufacturer’s instructions.
    IgA
    suggested: None

    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: 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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

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

    Results from rtransparent:
    • No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
    • 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 10.1101/2020.07.17.208439 on bioRxiv