Newborn Dried Blood Spots for Serologic Surveys of COVID-19

  1. Feimei Liu
  2. Mytien Nguyen
  3. Pavithra Vijayakumar
  4. Alanna Kaplan
  5. Amit Meir
  6. Yile Dai
  7. Eric Wang
  8. Hannah Walsh
  9. Aaron M. Ring
  10. Saad B. Omer
  11. Shelli F. Farhadian

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Abstract

There is an urgent need for inexpensive, population-wide surveillance testing for COVID-19. We tested newborn dried blood spot (DBS) anti-SARS-CoV-2 antibodies for all infants born at Yale from March to May 2020, and found that newborn DBS serologies reflect maternal and population-wide infection rates during the study period. This suggests a role for DBS in COVID-19 surveillance in areas where viral testing is limited.

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  1. Version published to 10.1097/inf.0000000000002918
  2. ScreenIT

    SciScore for 10.1101/2020.08.14.20175299: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was deemed exempt from human subjects regulations by the Yale institutional review board.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableRoutine SARS-CoV-2 PCR testing of all women who presented to labor and delivery began on April 1, 2020.

    Table 2: Resources

    Antibodies
    SentencesResources
    We adapted a standardized ELISA Serology Assay2 for detecting anti-SARS-CoV-2 antibody using newborn DBS. Anti-SARS-CoV-2 IgG was measured in all samples, and IgM was measured where the IgG result was positive.
    anti-SARS-CoV-2
    suggested: None
    Anti-SARS-CoV-2 IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    Maternal demographic and clinical features were examined in association with the likelihood of an antibody positive newborn using multivariable logistic regression performed in STATA 16.1.
    STATA
    suggested: (Stata, RRID:SCR_012763)

    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:
    This study has limitations. Most mothers were screened for SARS-CoV-2 at the time of hospitalization for delivery, but we were unable to determine the true date of maternal infection. Because we did not have access to the date of infection or serum antibody testing results for all mothers, we could not determine whether mothers who screened positive for SARS-CoV-2 by PCR but delivered a seronegative newborn had poor antibody responses themselves, had a remote infection with antibody responded that waned prior to delivery, or whether there was inefficient transplacental transfer of antibody in these cases. However, given that the majority of PCR positive mothers delivered seropositive newborns, this does not appear to diminish the utility of DBS as a surveillance tool. In this study, we demonstrate that levels of IgG in DBS reflect overall population-level trends in case incidence, with a lag that is consistent with the time to development of detectable antibodies after infection, making DBS antibody testing an attractive option for large-scale population surveillance during the COVID-19 pandemic. As dried blood spots are routinely collected from newborns, no additional sample collection is required, and specimens can be stored for later assessment. Using DBS as a surveillance tool may therefore be particularly advantageous in resource-poor settings, where innovative tools of field epidemiology will be required in order to control the spread of the virus.

    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.

  3. Version published to 10.1101/2020.08.14.20175299 on medRxiv