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Takahashi S, Peluso MJ, Hakim J, Turcios K, Janson O, Routledge I, Busch MP, Hoh R, Tai V, Kelly JD, Martin JN, Deeks SG, Henrich TJ, Greenhouse B, Rodríguez-Barraquer I. SARS-CoV-2 serology across scales: a framework for unbiased seroprevalence estimation incorporating antibody kinetics and epidemic recency. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.09.09.21263139. [PMID: 34545373 PMCID: PMC8452112 DOI: 10.1101/2021.09.09.21263139] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Serosurveys are a key resource for measuring SARS-CoV-2 cumulative incidence. A growing body of evidence suggests that asymptomatic and mild infections (together making up over 95% of all infections) are associated with lower antibody titers than severe infections. Antibody levels also peak a few weeks after infection and decay gradually. We developed a statistical approach to produce adjusted estimates of seroprevalence from raw serosurvey results that account for these sources of spectrum bias. We incorporate data on antibody responses on multiple assays from a post-infection longitudinal cohort, along with epidemic time series to account for the timing of a serosurvey relative to how recently individuals may have been infected. We applied this method to produce adjusted seroprevalence estimates from five large-scale SARS-CoV-2 serosurveys across different settings and study designs. We identify substantial differences between reported and adjusted estimates of over two-fold in the results of some surveys, and provide a tool for practitioners to generate adjusted estimates with pre-set or custom parameter values. While unprecedented efforts have been launched to generate SARS-CoV-2 seroprevalence estimates over this past year, interpretation of results from these studies requires properly accounting for both population-level epidemiologic context and individual-level immune dynamics.
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Affiliation(s)
- Saki Takahashi
- Division of HIV, Infectious Diseases & Global Medicine, University of California, San Francisco, USA
| | - Michael J. Peluso
- Division of HIV, Infectious Diseases & Global Medicine, University of California, San Francisco, USA
| | - Jill Hakim
- Division of HIV, Infectious Diseases & Global Medicine, University of California, San Francisco, USA
| | - Keirstinne Turcios
- Division of HIV, Infectious Diseases & Global Medicine, University of California, San Francisco, USA
| | - Owen Janson
- Division of HIV, Infectious Diseases & Global Medicine, University of California, San Francisco, USA
| | - Isobel Routledge
- Division of HIV, Infectious Diseases & Global Medicine, University of California, San Francisco, USA
| | - Michael P. Busch
- Department of Laboratory Medicine, University of California, San Francisco, USA
- Vitalant Research Institute, San Francisco, USA
| | - Rebecca Hoh
- Division of HIV, Infectious Diseases & Global Medicine, University of California, San Francisco, USA
| | - Viva Tai
- Division of HIV, Infectious Diseases & Global Medicine, University of California, San Francisco, USA
| | - J. Daniel Kelly
- Department of Epidemiology and Biostatistics, University of California, San Francisco, USA
- Institute for Global Health Sciences, University of California, San Francisco, USA
- F.I. Proctor Foundation, University of California, San Francisco, USA
| | - Jeffrey N. Martin
- Department of Epidemiology and Biostatistics, University of California, San Francisco, USA
| | - Steven G. Deeks
- Division of HIV, Infectious Diseases & Global Medicine, University of California, San Francisco, USA
| | - Timothy J. Henrich
- Division of Experimental Medicine, University of California, San Francisco, USA
| | - Bryan Greenhouse
- Division of HIV, Infectious Diseases & Global Medicine, University of California, San Francisco, USA
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