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Seroprevalence of immunoglobulin M and G antibodies against SARS-CoV-2 in China
Open accessAbstract
Detection of asymptomatic or subclinical novel human coronavirus SARS-CoV-2 infection is critical for understanding the overall prevalence and infection potential of COVID-19. To estimate the cumulative prevalence of SARS-CoV-2 infection in China, we evaluated the host serologic response, measured by the levels of immunoglobulins M and G in 17,368 individuals, in the city of Wuhan, the epicenter of the COVID-19 pandemic in China, and geographic regions in the country, during the period from 9 March 2020 to 10 April 2020. In our cohorts, the seropositivity in Wuhan varied between 3.2% and 3.8% in different subcohorts. Seroposivity progressively decreased in other cities as the distance to the epicenter increased. Patients who visited a hospital for maintenance hemodialysis and healthcare workers also had a higher seroprevalence of 3.3% (51 of 1,542, 2.5-4.3%, 95% confidence interval (CI)) and 1.8% (81 of 4,384, 1.5-2.3%, 95% CI), respectively. More studies are needed to determine whether these results are generalizable to other populations and geographic locations, as well as to determine at what rate seroprevalence is increasing with the progress of the COVID-19 pandemic. Serologic surveillance has the potential to provide a more faithful cumulative viral attack rate for the first season of this novel SARS-CoV-2 infection.
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“SARS-CoV-2 seroprevalence in our study is comparable with estimates from large population-based serosurveys in China, Switzerland, Spain, and the United States after the initial epidemic peak and after many tens of thousands of deaths (9, 10, 17, 18).”
From Seroprevalence of anti–SARS-CoV-2 IgG antibodies in Kenyan blood donors (2021) · cites this paper as [17]
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The Empirical Distribution Function with Arbitrarily Grouped, Censored and Truncated Data
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Metadata
- Authors
- Xu, X., Sun, J., Nie, S., Li, H., Kong, Y., Liang, M., Hou, J., Huang, X., Li, D., Ma, T., Peng, J., Gao, S., Shao, Y., Zhu, H., Lau, J. Y.-N., Wang, G., Xie, C., Jiang, L., Huang, A., Yang, Z., Zhang, K., & Hou, F. F.
- Affiliations
- Nanfang Hospital (CN)
- Kingmed Diagnostics (CN)
- First People's Hospital of Foshan (CN)
- Honghu People’s Hospital (CN)
- First People's Hospital of Jingzhou (CN)
- Jingzhou Central Hospital (CN)
- Honghu Hospital of Traditional Chinese Medicine (CN)
- Hong Kong Polytechnic University (HK)
- Tsinghua University (CN)
- University of Electronic Science and Technology of China (CN)
- Chongqing Medical University (CN)
- Macau University of Science and Technology (MO)
- Corresponding author
- Huang, Ailong
- Yang, Zhenglin
- Zhang, Kang
- Hou, Fan Fan
- ORCID
- Venue
- Nature Medicine
- Published
- 2020-06-05
- Volume
- 26
- Issue
- 8
- Pages
- 1193-1195
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W3033219406
- Cited by
- 405
- References
- 14
- Citations by year
- 2026: 2 · 2025: 9 · 2024: 16 · 2023: 28 · 2022: 58 · 2021: 174 · 2020: 118
- FWCI
- 12.42
- Type
- journal article
- Language
- en
- Update notices
- correction (2020-08-18)
- Open access
- bronze
- doi.org
- Locations
- Nature Medicine (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Fundo para o Desenvolvimento das Ciências e da Tecnologia (0035/2020/A)
- Guangzhou Regenerative Medicine and Health Guangdong Laboratory (2020GZR110306001, 2018GZR110102004, 2018GZR0201003)
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 detection and testing
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Keywords
- SARS-CoV-2, COVID-19 pandemic, seroprevalence, immunoglobulin M, IgG, serological surveillance, asymptomatic infection, Wuhan, hemodialysis patients, healthcare workers, regional variation
- MeSH terms
- Betacoronavirus, COVID-19, SARS-CoV-2, Antibodies, Viral, China, Female, Health Personnel, Humans, Immunoglobulin G, Immunoglobulin M, Male, Middle Aged, Pneumonia, Viral, Seroepidemiologic Studies, Coronavirus Infections, Pandemics
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