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Antibody Responses to SARS-CoV-2 in Patients With Novel Coronavirus Disease 2019
Open accessPublished version of a preprint
Abstract
Background: The novel coronavirus SARS-CoV-2 is a newly emerging virus. The antibody response in infected patients remains largely unknown, and the clinical value of antibody testing has not been fully demonstrated. Methods: 173 patients with SARS-CoV-2 infection were enrolled. Their serial plasma samples (n = 535) collected during hospitalization were tested for total antibodies (Ab), IgM, and IgG against SARS-CoV-2. The dynamics of antibodies with disease progress were analyzed. Results: Among 173 patients, the seroconversion rates for Ab, IgM, and IgG were 93.1%, 82.7%, and 64.7%, respectively. The reason for the negative antibody findings in 12 patients might be due to the lack of blood samples at the later stage of illness. The median seroconversion times for Ab, IgM, and then IgG were days 11, 12, and 4, respectively. The presence of antibodies was <40% among patients within 1 week of onset, and rapidly increased to 100.0% (Ab), 94.3% (IgM), and 79.8% (IgG) by day 15 after onset. In contrast, RNA detectability decreased from 66.7% (58/87) in samples collected before day 7 to 45.5% (25/55) during days 15–39. Combining RNA and antibody detection significantly improved the sensitivity of pathogenic diagnosis for COVID-19 (P < .001), even in the early phase of 1 week from onset (P = .007). Moreover, a higher titer of Ab was independently associated with a worse clinical classification (P = .006). Conclusions: Antibody detection offers vital clinical information during the course of SARS-CoV-2 infection. The findings provide strong empirical support for the routine application of serological testing in the diagnosis and management of COVID-19 patients.
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“We aligned cases and seroprevalence on the basis of individual record data suggesting that exposure to a laboratory-confirmed case was typically 10–13 days36 and exposure to seroconversion was 14–17 days.37, 38, 39”
From Estimating global, regional, and national daily and cumulative infections with SARS-CoV-2 through Nov 14, 2021: a statistical analysis (2022) · cites this paper as [37]
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Metadata
- Authors
- Zhao, J., Yuan, Q., Wang, H., Liu, W., Liao, X., Su, Y., Wang, X., Yuan, J., Li, T., Li, J., Qian, S., Hong, C., Wang, F., Liu, Y., Wang, Z., He, Q., Li, Z., He, B., Zhang, T., Fu, Y., Ge, S., Liu, L., Zhang, J., Xia, N., & Zhang, Z.
- Affiliations
- Shenzhen Third People’s Hospital (CN)
- Xiamen University (CN)
- Southern University of Science and Technology (CN)
- Corresponding author
- Zhang, Zheng
- ORCID
- Venue
- Clinical Infectious Diseases
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-05-28
- Volume
- 71
- Issue
- 16
- Pages
- 2027-2034
- ISSN
- 1058-4838 (ISSN-L)
- 1537-6591
- PMC
- PMC7184337
- OpenAlex
- W3013985547
- Cited by
- 2,607
- References
- 13
- Citations by year
- 2026: 14 · 2025: 54 · 2024: 95 · 2023: 175 · 2022: 359 · 2021: 862 · 2020: 1046
- FWCI
- 80.11
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Clinical Infectious Diseases (publishedVersion)
- medRxiv (acceptedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Bill and Melinda Gates Foundation
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 detection and testing
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Keywords
- SARS-CoV-2, COVID-19 pandemic, antibody response, seroconversion, IgM, IgG, serological diagnosis, viral RNA detection, disease severity, antibody titers, diagnostic sensitivity
- MeSH terms
- COVID-19, SARS-CoV-2, Adult, Aged, Antibodies, Viral, Antibody Formation, Enzyme-Linked Immunosorbent Assay, Female, Humans, Immunoglobulin G, Immunoglobulin M, Male, Middle Aged, Serologic Tests, Pandemics
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