Citywide serosurveillance of the initial SARS-CoV-2 outbreak in San Francisco using electronic health records

Population-based surveys are the gold standard for estimating seroprevalence but are expensive and often only capture a small geographic area or window of time. This study describes a new platform, SCALE-IT, for serosurveillance based on algorithmic sampling of electronic health records, and uses it...

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Bibliographic Details
Main Authors: Isobel Routledge, Adrienne Epstein, Saki Takahashi, Owen Janson, Jill Hakim, Elias Duarte, Keirstinne Turcios, Joanna Vinden, Kirk Sujishi, Jesus Rangel, Marcelina Coh, Lee Besana, Wai-Kit Ho, Ching-Ying Oon, Chui Mei Ong, Cassandra Yun, Kara Lynch, Alan H. B. Wu, Wesley Wu, William Karlon, Edward Thornborrow, Michael J. Peluso, Timothy J. Henrich, John E. Pak, Jessica Briggs, Bryan Greenhouse, Isabel Rodriguez-Barraquer
Format: Article
Language:English
Published: Nature Publishing Group 2021-06-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-021-23651-6
Description
Summary:Population-based surveys are the gold standard for estimating seroprevalence but are expensive and often only capture a small geographic area or window of time. This study describes a new platform, SCALE-IT, for serosurveillance based on algorithmic sampling of electronic health records, and uses it to estimate the seroprevalence of SARS-CoV-2 in San Francisco.
ISSN:2041-1723