COVID-19 antibody seroprevalence in Santa Clara County, California

Eran Bendavid; Bianca Mulaney; Neeraj Sood; Soleil Shah; Rebecca Bromley-Dulfano; Cara Lai; Zoe Weissberg; Rodrigo Saavedra-Walker; Jim Tedrow; Andrew Bogan; Thomas Kupiec; Daniel Eichner; Ribhav Gupta; John P A Ioannidis; Jay Bhattacharya

doi:10.1093/ije/dyab010

COVID-19 antibody seroprevalence in Santa Clara County, California

Int J Epidemiol. 2021 May 17;50(2):410-419. doi: 10.1093/ije/dyab010.

Authors

Affiliations

¹ Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
² Stanford University School of Medicine, Stanford, CA, USA.
³ Sol Price School of Public Policy, University of Southern California, Los Angeles, CA, USA.
⁴ Health Education is Power, Inc., Palo Alto, CA, USA.
⁵ The Compliance Resource Group, Inc., Oklahoma City, OK, USA.
⁶ Bogan Associates, LLC, Palo Alto, CA, USA.
⁷ ARL BioPharma, Inc., Oklahoma City, OK, USA.
⁸ Sports Medicine Research and Testing Laboratory, Salt Lake City, UT, USA.
⁹ Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA.

Abstract

Background: Measuring the seroprevalence of antibodies to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is central to understanding infection risk and fatality rates. We studied Coronavirus Disease 2019 (COVID-19)-antibody seroprevalence in a community sample drawn from Santa Clara County.

Methods: On 3 and 4 April 2020, we tested 3328 county residents for immunoglobulin G (IgG) and immunoglobulin M (IgM) antibodies to SARS-CoV-2 using a rapid lateral-flow assay (Premier Biotech). Participants were recruited using advertisements that were targeted to reach county residents that matched the county population by gender, race/ethnicity and zip code of residence. We estimate weights to match our sample to the county by zip, age, sex and race/ethnicity. We report the weighted and unweighted prevalence of antibodies to SARS-CoV-2. We adjust for test-performance characteristics by combining data from 18 independent test-kit assessments: 14 for specificity and 4 for sensitivity.

Results: The raw prevalence of antibodies in our sample was 1.5% [exact binomial 95% confidence interval (CI) 1.1-2.0%]. Test-performance specificity in our data was 99.5% (95% CI 99.2-99.7%) and sensitivity was 82.8% (95% CI 76.0-88.4%). The unweighted prevalence adjusted for test-performance characteristics was 1.2% (95% CI 0.7-1.8%). After weighting for population demographics, the prevalence was 2.8% (95% CI 1.3-4.2%), using bootstrap to estimate confidence bounds. These prevalence point estimates imply that 53 000 [95% CI 26 000 to 82 000 using weighted prevalence; 23 000 (95% CI 14 000-35 000) using unweighted prevalence] people were infected in Santa Clara County by late March-many more than the ∼1200 confirmed cases at the time.

Conclusion: The estimated prevalence of SARS-CoV-2 antibodies in Santa Clara County implies that COVID-19 was likely more widespread than indicated by the number of cases in late March, 2020. At the time, low-burden contexts such as Santa Clara County were far from herd-immunity thresholds.

Keywords: COVID-19; infection fatality rate; seroprevalence.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Antibodies, Viral
COVID-19*
California / epidemiology
Humans
SARS-CoV-2
Seroepidemiologic Studies

Substances

Antibodies, Viral