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Cited by 185

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SARS-CoV-2 seroprevalence and neutralizing activity in donor and patient blood

Open access
Ng, Dianna L., Goldgof, Gregory M., Shy, Brian R., Levine, Andrew G., Balcerek, Joanna, Bapat, Sagar P., Prostko, John, Rodgers, Mary, Coller, Kelly, Pearce, Sandra, Franz, Sergej, Du, Li, Stone, Mars, Pillai, Satish K., Sotomayor-Gonzalez, Alicia, Servellita, Venice, Martin, Claudia Sanchez San, Granados, Andrea, Glasner, Dustin R., Han, Lucy M., Truong, Kent, Akagi, Naomi, Nguyen, David N., Neumann, Neil M., Qazi, Daniel, Hsu, Elaine, Gu, Wei, Santos, Yale A., Custer, Brian, Green, Valerie, Williamson, Phillip, Hills, Nancy K., Lu, Chuanyi M., Whitman, Jeffrey D., Stramer, Susan L., Wang, Candace, Reyes, Kevin, Hakim, Jill M. C., Sujishi, Kirk, Alazzeh, Fariba, Pham, Lori, Thornborrow, Edward, Oon, Ching-Ying, Miller, Steve, Kurtz, Theodore, Simmons, Graham, Hackett, John, Busch, Michael P., Chiu, Charles Y.·2020·Nature Communications
DOI 10.1038/s41467-020-18468-8

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Abstract

Given the limited availability of serological testing to date, the seroprevalence of SARS-CoV-2-specific antibodies in different populations has remained unclear. Here, we report very low SARS-CoV-2 seroprevalence in two San Francisco Bay Area populations. Seroreactivity was 0.26% in 387 hospitalized patients admitted for non-respiratory indications and 0.1% in 1,000 blood donors in early April 2020. We additionally describe the longitudinal dynamics of immunoglobulin-G (IgG), immunoglobulin-M (IgM), and in vitro neutralizing antibody titers in COVID-19 patients. The median time to seroconversion ranged from 10.3–11.0 days for these 3 assays. Neutralizing antibodies rose in tandem with immunoglobulin titers following symptom onset, and positive percent agreement between detection of IgG and neutralizing titers was >93%. These findings emphasize the importance of using highly accurate tests for surveillance studies in low-prevalence populations, and provide evidence that seroreactivity using SARS-CoV-2 anti-nucleocapsid protein IgG and anti-spike IgM assays are generally predictive of in vitro neutralizing capacity.

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Research works printed but not linked: 16

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Metadata

Authors
Ng, D. L., Goldgof, G. M., Shy, B. R., Levine, A. G., Balcerek, J., Bapat, S. P., Prostko, J., Rodgers, M., Coller, K., Pearce, S., Franz, S., Du, L., Stone, M., Pillai, S. K., Sotomayor-Gonzalez, A., Servellita, V., Martin, C. S. S., Granados, A., Glasner, D. R., Han, L. M., Truong, K., Akagi, N., Nguyen, D. N., Neumann, N. M., Qazi, D., Hsu, E., Gu, W., Santos, Y. A., Custer, B., Green, V., Williamson, P., Hills, N. K., Lu, C. M., Whitman, J. D., Stramer, S. L., Wang, C., Reyes, K., Hakim, J. M. C., Sujishi, K., Alazzeh, F., Pham, L., Thornborrow, E., Oon, C.-Y., Miller, S., Kurtz, T., Simmons, G., Hackett, J., Busch, M. P., & Chiu, C. Y.
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2020-09-17
Volume
11
Issue
1
Pages
4698-4698
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-020-18468-8
OpenAlex
W3087153161
Cited by
185
References
2
FWCI
5.01
Type
journal article
Language
en
Open access
gold
Licence
Funders
  • U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (R01HL10504)
  • U.S. Department of Health & Human Services | NIH | National Institute of Allergy and Infectious Diseases (R33AI129077)
  • Abbott Laboratories

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CoChat. (2026). Citation check: SARS-CoV-2 seroprevalence and neutralizing activity in donor and patient blood. https://app.cochat.ai/papers/10.1038/s41467-020-18468-8
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Ng, D. L., Goldgof, G. M., Shy, B. R., Levine, A. G., Balcerek, J., Bapat, S. P., Prostko, J., Rodgers, M., Coller, K., Pearce, S., Franz, S., Du, L., Stone, M., Pillai, S. K., Sotomayor-Gonzalez, A., Servellita, V., Martin, C. S. S., Granados, A., Glasner, D. R., . . . Chiu, C. Y. (2020). SARS-CoV-2 seroprevalence and neutralizing activity in donor and patient blood. Nature Communications. https://doi.org/10.1038/s41467-020-18468-8

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.