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Citywide serosurveillance of the initial SARS-CoV-2 outbreak in San Francisco using electronic health records
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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8195995/ https://www.ncbi.nlm.nih.gov/pubmed/34117227 http://dx.doi.org/10.1038/s41467-021-23651-6 |
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author | Routledge, Isobel Epstein, Adrienne Takahashi, Saki Janson, Owen Hakim, Jill Duarte, Elias Turcios, Keirstinne Vinden, Joanna Sujishi, Kirk Rangel, Jesus Coh, Marcelina Besana, Lee Ho, Wai-Kit Oon, Ching-Ying Ong, Chui Mei Yun, Cassandra Lynch, Kara Wu, Alan H. B. Wu, Wesley Karlon, William Thornborrow, Edward Peluso, Michael J. Henrich, Timothy J. Pak, John E. Briggs, Jessica Greenhouse, Bryan Rodriguez-Barraquer, Isabel |
author_facet | Routledge, Isobel Epstein, Adrienne Takahashi, Saki Janson, Owen Hakim, Jill Duarte, Elias Turcios, Keirstinne Vinden, Joanna Sujishi, Kirk Rangel, Jesus Coh, Marcelina Besana, Lee Ho, Wai-Kit Oon, Ching-Ying Ong, Chui Mei Yun, Cassandra Lynch, Kara Wu, Alan H. B. Wu, Wesley Karlon, William Thornborrow, Edward Peluso, Michael J. Henrich, Timothy J. Pak, John E. Briggs, Jessica Greenhouse, Bryan Rodriguez-Barraquer, Isabel |
author_sort | Routledge, Isobel |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8195995 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-81959952021-06-17 Citywide serosurveillance of the initial SARS-CoV-2 outbreak in San Francisco using electronic health records Routledge, Isobel Epstein, Adrienne Takahashi, Saki Janson, Owen Hakim, Jill Duarte, Elias Turcios, Keirstinne Vinden, Joanna Sujishi, Kirk Rangel, Jesus Coh, Marcelina Besana, Lee Ho, Wai-Kit Oon, Ching-Ying Ong, Chui Mei Yun, Cassandra Lynch, Kara Wu, Alan H. B. Wu, Wesley Karlon, William Thornborrow, Edward Peluso, Michael J. Henrich, Timothy J. Pak, John E. Briggs, Jessica Greenhouse, Bryan Rodriguez-Barraquer, Isabel Nat Commun Article 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. Nature Publishing Group UK 2021-06-11 /pmc/articles/PMC8195995/ /pubmed/34117227 http://dx.doi.org/10.1038/s41467-021-23651-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Routledge, Isobel Epstein, Adrienne Takahashi, Saki Janson, Owen Hakim, Jill Duarte, Elias Turcios, Keirstinne Vinden, Joanna Sujishi, Kirk Rangel, Jesus Coh, Marcelina Besana, Lee Ho, Wai-Kit Oon, Ching-Ying Ong, Chui Mei Yun, Cassandra Lynch, Kara Wu, Alan H. B. Wu, Wesley Karlon, William Thornborrow, Edward Peluso, Michael J. Henrich, Timothy J. Pak, John E. Briggs, Jessica Greenhouse, Bryan Rodriguez-Barraquer, Isabel Citywide serosurveillance of the initial SARS-CoV-2 outbreak in San Francisco using electronic health records |
title | Citywide serosurveillance of the initial SARS-CoV-2 outbreak in San Francisco using electronic health records |
title_full | Citywide serosurveillance of the initial SARS-CoV-2 outbreak in San Francisco using electronic health records |
title_fullStr | Citywide serosurveillance of the initial SARS-CoV-2 outbreak in San Francisco using electronic health records |
title_full_unstemmed | Citywide serosurveillance of the initial SARS-CoV-2 outbreak in San Francisco using electronic health records |
title_short | Citywide serosurveillance of the initial SARS-CoV-2 outbreak in San Francisco using electronic health records |
title_sort | citywide serosurveillance of the initial sars-cov-2 outbreak in san francisco using electronic health records |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8195995/ https://www.ncbi.nlm.nih.gov/pubmed/34117227 http://dx.doi.org/10.1038/s41467-021-23651-6 |
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