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Sentinel surveillance of SARS-CoV-2 rates and equity impacts using labor and delivery patients in Phoenix, Arizona

Proactive management of SARS-CoV-2 requires timely and complete population data to track the evolution of the virus and identify at risk populations. However, many cases are asymptomatic and are not easily discovered through traditional testing efforts. Sentinel surveillance can be used to estimate...

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Autores principales: Linehan, Caitlyn J., Nelson, Trisalyn, Bailey, Celeste V., Gel, Esma, Coonrod, Dean V., Roth, Cheryl K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9637539/
https://www.ncbi.nlm.nih.gov/pubmed/36377230
http://dx.doi.org/10.1016/j.pmedr.2022.102049
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author Linehan, Caitlyn J.
Nelson, Trisalyn
Bailey, Celeste V.
Gel, Esma
Coonrod, Dean V.
Roth, Cheryl K.
author_facet Linehan, Caitlyn J.
Nelson, Trisalyn
Bailey, Celeste V.
Gel, Esma
Coonrod, Dean V.
Roth, Cheryl K.
author_sort Linehan, Caitlyn J.
collection PubMed
description Proactive management of SARS-CoV-2 requires timely and complete population data to track the evolution of the virus and identify at risk populations. However, many cases are asymptomatic and are not easily discovered through traditional testing efforts. Sentinel surveillance can be used to estimate the prevalence of infections for geographical areas but requires identification of sentinels who are representative of the larger population. Our goal is to evaluate applicability of a population of labor and delivery patients for sentinel surveillance system for monitoring the prevalence of SARS-CoV-2 infection. We tested 5307 labor and delivery patients from two hospitals in Phoenix, Arizona, finding 195 SARS-CoV-2 positive. Most positive cases were associated with people who were asymptomatic (79.44%), similar to statewide rates. Our results add to the growing body of evidence that SARS-CoV-2 disproportionately impacts people of color, with Black people having the highest positive rates (5.92%). People with private medical insurance had the lowest positive rates (2.53%), while Medicaid patients had a positive rate of 5.54% and people without insurance had the highest positive rates (6.12%). With diverse people reporting for care and being tested regardless of symptoms, labor and delivery patients may serve as ideal sentinels for asymptomatic detection of SARS-CoV-2 and monitoring impacts across a wide range of social and economic classes. A more robust system for infectious disease management requires the expanded participation of additional hospitals so that the sentinels are more representative of the population at large, reflecting geographic and neighborhood level patterns of infection and risk.
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spelling pubmed-96375392022-11-07 Sentinel surveillance of SARS-CoV-2 rates and equity impacts using labor and delivery patients in Phoenix, Arizona Linehan, Caitlyn J. Nelson, Trisalyn Bailey, Celeste V. Gel, Esma Coonrod, Dean V. Roth, Cheryl K. Prev Med Rep Regular Article Proactive management of SARS-CoV-2 requires timely and complete population data to track the evolution of the virus and identify at risk populations. However, many cases are asymptomatic and are not easily discovered through traditional testing efforts. Sentinel surveillance can be used to estimate the prevalence of infections for geographical areas but requires identification of sentinels who are representative of the larger population. Our goal is to evaluate applicability of a population of labor and delivery patients for sentinel surveillance system for monitoring the prevalence of SARS-CoV-2 infection. We tested 5307 labor and delivery patients from two hospitals in Phoenix, Arizona, finding 195 SARS-CoV-2 positive. Most positive cases were associated with people who were asymptomatic (79.44%), similar to statewide rates. Our results add to the growing body of evidence that SARS-CoV-2 disproportionately impacts people of color, with Black people having the highest positive rates (5.92%). People with private medical insurance had the lowest positive rates (2.53%), while Medicaid patients had a positive rate of 5.54% and people without insurance had the highest positive rates (6.12%). With diverse people reporting for care and being tested regardless of symptoms, labor and delivery patients may serve as ideal sentinels for asymptomatic detection of SARS-CoV-2 and monitoring impacts across a wide range of social and economic classes. A more robust system for infectious disease management requires the expanded participation of additional hospitals so that the sentinels are more representative of the population at large, reflecting geographic and neighborhood level patterns of infection and risk. 2022-11-07 /pmc/articles/PMC9637539/ /pubmed/36377230 http://dx.doi.org/10.1016/j.pmedr.2022.102049 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Linehan, Caitlyn J.
Nelson, Trisalyn
Bailey, Celeste V.
Gel, Esma
Coonrod, Dean V.
Roth, Cheryl K.
Sentinel surveillance of SARS-CoV-2 rates and equity impacts using labor and delivery patients in Phoenix, Arizona
title Sentinel surveillance of SARS-CoV-2 rates and equity impacts using labor and delivery patients in Phoenix, Arizona
title_full Sentinel surveillance of SARS-CoV-2 rates and equity impacts using labor and delivery patients in Phoenix, Arizona
title_fullStr Sentinel surveillance of SARS-CoV-2 rates and equity impacts using labor and delivery patients in Phoenix, Arizona
title_full_unstemmed Sentinel surveillance of SARS-CoV-2 rates and equity impacts using labor and delivery patients in Phoenix, Arizona
title_short Sentinel surveillance of SARS-CoV-2 rates and equity impacts using labor and delivery patients in Phoenix, Arizona
title_sort sentinel surveillance of sars-cov-2 rates and equity impacts using labor and delivery patients in phoenix, arizona
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9637539/
https://www.ncbi.nlm.nih.gov/pubmed/36377230
http://dx.doi.org/10.1016/j.pmedr.2022.102049
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