In late 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first detected in China and has since caused a pandemic of coronavirus disease 2019 (COVID-19). The first case of COVID-19 in New York City was officially confirmed on 1 March 2020 followed by a severe local epidemic1. Here, to understand seroprevalence dynamics, we conduct a retrospective, repeated cross-sectional analysis of anti-SARS-CoV-2 spike antibodies in weekly intervals from the beginning of February to July 2020 using more than 10,000 plasma samples from patients at Mount Sinai Hospital in New York City. We describe the dynamics of seroprevalence in an ‘urgent care’ group, which is enriched in cases of COVID-19 during the epidemic, and a ‘routine care’ group, which more closely represents the general population. Seroprevalence increased at different rates in both groups; seropositive samples were found as early as mid-February, and levelled out at slightly above 20% in both groups after the epidemic wave subsided by the end of May. From May to July, seroprevalence remained stable, suggesting lasting antibody levels in the population. Our data suggest that SARS-CoV-2 was introduced in New York City earlier than previously documented and describe the dynamics of seroconversion over the full course of the first wave of the pandemic in a major metropolitan area.
New York City demographic data were sourced from the NYC 2010 census data (https://www1.nyc.gov/site/planning/planning-level/nyc-population/census-2010.page). The numbers of confirmed COVID-19 cases and mortalities were sourced from the NYC COVID-19 page (https://www1.nyc.gov/site/doh/covid/covid-19-data.page). Source data are provided with this paper.
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We thank L. Rudon, H. Glazowski and the team members of the Blood Bank and Rapid Response Laboratories of the Mount Sinai Health System for their assistance with the acquisition of plasma samples, P. Palese and C. Cordon-Cardo for their continued support and encouragement, the Technology Development Facility led by R. Sebra for providing additional BSL2 space for sample collection, the Scientific Computing Group at the Icahn School of Medicine at Mount Sinai for providing an electronic honest broker system, and members of the ISMMS Program for the Protection of Human Subjects (PPHS) for their continuous expert guidance. This work was partially supported by the NIAID Centers of Excellence for Influenza Research and Surveillance (CEIRS) contract HHSN272201400008C (to F.K., for reagent generation), Collaborative Influenza Vaccine Innovation Centers (CIVIC) contract 75N93019C00051 (to F.K., for reagent generation), and the support of the JPB foundation, the Open Philanthropy Project (2020-215611) and other philanthropic donations. This effort was deliberated with Leidos Biomedical Research/NCI over the last several months and is now going to be supported by the Serological Sciences Network (SeroNet). This project will be funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under contract no. 75N91019D00024, task order no. 75N91020F00003 and under U54 CA260560-01. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products or organizations imply endorsement by the US Government.
Mount Sinai has licensed serological assays to commercial entities and has filed for patent protection for serological assays. D.S., F.A., V.S. and F.K. are listed as inventors on the pending patent application (US provisional application no. 63/059,924). C.C., K.J., J.T., M.M.H., M.M., G.A.A., S.F., K.T., J.J., M.D.N., E.M.S., H.v.B. and C.T. declare no competing interests.
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Extended data figures and tables
Extended Data Fig. 1 Seroprevalence and COVID-19 diagnoses in the urgent care group per week of the observation period.
The percentage of individuals positive for antibodies and the percentage of cases diagnosed with COVID-19 are shown.
Extended Data Fig. 2 Antibody titres and increase in seroprevalence in the routine care group in relationship to the number of confirmed cases in NYC.
a, Percentage seroprevalence in the routine care group compared with the number of detected cases in NYC per week of the observation period. b, Geometric mean antibody titres (GMT) of positive cases in the routine care group versus detected cases in NYC per week of the observation period. c, Increase in seroprevalence compared with the cumulative number of cases and the cumulative numbers of cases with 7-, 14- or 21-day delays. Data for the number of confirmed cases in NYC were retrieved from https://www1.nyc.gov/site/doh/covid/covid-19-data.page.
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Stadlbauer, D., Tan, J., Jiang, K. et al. Repeated cross-sectional sero-monitoring of SARS-CoV-2 in New York City. Nature (2020). https://doi.org/10.1038/s41586-020-2912-6