Citywide serosurveillance of the initial SARS-CoV-2 outbreak in San Francisco using electronic health records
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 L. Lynch, Alan H.B. Wu, Wesley Wu, William Karlon, Edward C. Thornborrow, Michael J. Peluso, Timothy J. Henrich, John E. Pak, Jessica Briggs, Bryan Greenhouse, Isabel Rodríguez-Barraquer
Abstract
Serosurveillance provides a unique opportunity to quantify the proportion of the population that has been exposed to pathogens. Here, we developed and piloted Serosurveillance for Continuous, ActionabLe Epidemiologic Intelligence of Transmission (SCALE-IT), a platform through which we systematically tested remnant samples from routine blood draws in two major hospital networks in San Francisco for SARS-CoV-2 antibodies during the early months of the pandemic. Importantly, SCALE-IT allows for algorithmic sample selection and rich data on covariates by leveraging electronic health record data. We estimated overall seroprevalence at 4.2%, corresponding to a case ascertainment rate of only 4.9%, and identified important heterogeneities by neighborhood, homelessness status, and race/ethnicity. Neighborhood seroprevalence estimates from SCALE-IT were comparable to local community-based surveys, while providing results encompassing the entire city that have been previously unavailable. Leveraging this hybrid serosurveillance approach has strong potential for application beyond this local context and for diseases other than SARS-CoV-2.