Evidence map›Paper›PMID 32511472›Full record

ArticlemedRxiv : the preprint server for health sciences2020

Standardization of enzyme-linked immunosorbent assays for serosurveys of the SARS-CoV-2 pandemic using clinical and at-home blood sampling.

Carleen Klumpp-Thomas, Heather Kalish, Matthew Drew, Sally Hunsberger, Kelly Snead, Michael P Fay, Jennifer Mehalko, Anandakumar Shunmugavel, Vanessa Wall, Peter Frank and 11 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

21 authors.

Carleen Klumpp-ThomasNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville MD, 20850.
Heather KalishTrans-NIH Shared Resource on Biomedical Engineering and Physical Science, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda MD 20894.
Matthew DrewProtein Expression Laboratory, NCI RAS Initiative, Frederick National Laboratory for Cancer Research, Frederick, MD 21702.
Sally HunsbergerBiostatistics Research Branch, National Institute for Allergy and Infectious Disease, National Institutes of Health, Bethesda, MD 20894.
Kelly SneadProtein Expression Laboratory, NCI RAS Initiative, Frederick National Laboratory for Cancer Research, Frederick, MD 21702.
Michael P FayBiostatistics Research Branch, National Institute for Allergy and Infectious Disease, National Institutes of Health, Bethesda, MD 20894.
Jennifer MehalkoProtein Expression Laboratory, NCI RAS Initiative, Frederick National Laboratory for Cancer Research, Frederick, MD 21702.
Anandakumar ShunmugavelSection on Immuno-Engineering, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda MD 20894.
Vanessa WallProtein Expression Laboratory, NCI RAS Initiative, Frederick National Laboratory for Cancer Research, Frederick, MD 21702.
Peter FrankProtein Expression Laboratory, NCI RAS Initiative, Frederick National Laboratory for Cancer Research, Frederick, MD 21702.
John-Paul DensonProtein Expression Laboratory, NCI RAS Initiative, Frederick National Laboratory for Cancer Research, Frederick, MD 21702.
Min HongProtein Expression Laboratory, NCI RAS Initiative, Frederick National Laboratory for Cancer Research, Frederick, MD 21702.
Gulcin GultenProtein Expression Laboratory, NCI RAS Initiative, Frederick National Laboratory for Cancer Research, Frederick, MD 21702.
Simon MessingProtein Expression Laboratory, NCI RAS Initiative, Frederick National Laboratory for Cancer Research, Frederick, MD 21702.
Jennifer HicksTrans-NIH Shared Resource on Biomedical Engineering and Physical Science, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda MD 20894.
Sam MichaelNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville MD, 20850.
William GilletteProtein Expression Laboratory, NCI RAS Initiative, Frederick National Laboratory for Cancer Research, Frederick, MD 21702.
Matthew D HallNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville MD, 20850.
Matthew MemoliLID Clinical Studies Unit, Laboratory of Infectious Diseases, Division of Intramural Research, National Institute for Allergy and Infectious Disease, National Institutes of Health, Bethesda, MD 20894.
Dominic EspositoProtein Expression Laboratory, NCI RAS Initiative, Frederick National Laboratory for Cancer Research, Frederick, MD 21702.
Kaitlyn SadtlerSection on Immuno-Engineering, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda MD 20894.

Funding

Research Services Section (RSS)ZICTR000242 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI WILSON, KELLI · 2015 to 2025
$64.9M
ImmunoengineeringZIAEB000093 · NIBIB · NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING · PI SADTLER, KAITLYN · 2020 to 2025
$5.5M
Coronavirus Pathogenesis and Broadly Protective Vaccine DevelopmentZIAAI001268 · NIAID · NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES · PI MEMOLI, MATTHEW · 2020 to 2025
$4.8M
CCR NIH HHS HHSN261200800001CNCI NIH HHS HHSN261200800001E
6 · The paper itself

Abstract

The extent of SARS-CoV-2 infection throughout the United States population is currently unknown. High quality serology is a key tool to understanding the spread of infection, immunity against the virus, and correlates of protection. Limited validation and testing of serology assays used for serosurveys can lead to unreliable or misleading data, and clinical testing using such unvalidated assays can lead to medically costly diagnostic errors and improperly informed public health decisions. Estimating prevalence and clinical decision making is highly dependent on specificity. Here, we present an optimized ELISA-based serology protocol from antigen production to data analysis. This protocol defines thresholds for IgG and IgM for determination of seropositivity with estimated specificity well above 99%. Validation was performed using both traditionally collected serum and dried blood on mail-in blood sampling kits, using archival (pre-2019) negative controls and known PCR-diagnosed positive patient controls. Minimal cross-reactivity was observed for the spike proteins of MERS, SARS1, OC43 and HKU1 viruses and no cross reactivity was observed with anti-influenza A H1N1 HAI titer during validation. This strategy is highly specific and is designed to provide good estimates of seroprevalence of SARS-CoV-2 seropositivity in a population, providing specific and reliable data from serosurveys and clinical testing which can be used to better evaluate and understand SARS-CoV-2 immunity and correlates of protection.

Identifiers

PMID32511472
PMCPMC7265693

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.