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Use of wastewater metrics to track COVID-19 in the U.S.: a national time-series analysis over the first three quarters of 2022
BACKGROUND: Widespread use of at-home COVID-19 tests hampers determination of community COVID-19 incidence. Using nationwide data available through the US National Wastewater Surveillance System, we examined the performance of two wastewater metrics in predicting high case and hospitalizations rates...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9934789/ https://www.ncbi.nlm.nih.gov/pubmed/36798337 http://dx.doi.org/10.1101/2023.02.06.23285542 |
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author | Varkila, Meri Montez-Rath, Maria Salomon, Joshua Yu, Xue Block, Geoffrey Owens, Douglas K. Chertow, Glenn M Parsonnet, Julie Anand, Shuchi |
author_facet | Varkila, Meri Montez-Rath, Maria Salomon, Joshua Yu, Xue Block, Geoffrey Owens, Douglas K. Chertow, Glenn M Parsonnet, Julie Anand, Shuchi |
author_sort | Varkila, Meri |
collection | PubMed |
description | BACKGROUND: Widespread use of at-home COVID-19 tests hampers determination of community COVID-19 incidence. Using nationwide data available through the US National Wastewater Surveillance System, we examined the performance of two wastewater metrics in predicting high case and hospitalizations rates both before and after widespread use of at-home tests. METHODS: We performed area under the receiver operating characteristic (ROC) curve analysis (AUC) for two wastewater metrics—viral concentration relative to the peak of January 2022 (“wastewater percentile”) and 15-day percent change in SARS-CoV-2 (“percent change”). Dichotomized reported cases (≥ 200 or <200 cases per 100,000) and new hospitalizations (≥ 10 or <10 per 100,000) were our dependent variables, stratified by calendar quarter. Using logistic regression, we assessed the performance of combining wastewater metrics. RESULTS: Among 268 counties across 22 states, wastewater percentile detected high reported case and hospitalizations rates in the first quarter of 2022 (AUC 0.95 and 0.86 respectively) whereas the percent change did not (AUC 0.54 and 0.49 respectively). A wastewater percentile of 51% maximized sensitivity (0.93) and specificity (0.82) for detecting high case rates. A model inclusive of both metrics performed no better than using wastewater percentile alone. The predictive capability of wastewater percentile declined over time (AUC 0.84 and 0.72 for cases for second and third quarters of 2022). CONCLUSION: Nationwide, county wastewater levels above 51% relative to the historic peak predicted high COVID rates and hospitalization in the first quarter of 2022, but performed less well in subsequent quarters. Decline over time in predictive performance of this metric likely reflects underreporting of cases, reduced testing, and possibly lower virulence of infection due to vaccines and treatments. |
format | Online Article Text |
id | pubmed-9934789 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-99347892023-02-17 Use of wastewater metrics to track COVID-19 in the U.S.: a national time-series analysis over the first three quarters of 2022 Varkila, Meri Montez-Rath, Maria Salomon, Joshua Yu, Xue Block, Geoffrey Owens, Douglas K. Chertow, Glenn M Parsonnet, Julie Anand, Shuchi medRxiv Article BACKGROUND: Widespread use of at-home COVID-19 tests hampers determination of community COVID-19 incidence. Using nationwide data available through the US National Wastewater Surveillance System, we examined the performance of two wastewater metrics in predicting high case and hospitalizations rates both before and after widespread use of at-home tests. METHODS: We performed area under the receiver operating characteristic (ROC) curve analysis (AUC) for two wastewater metrics—viral concentration relative to the peak of January 2022 (“wastewater percentile”) and 15-day percent change in SARS-CoV-2 (“percent change”). Dichotomized reported cases (≥ 200 or <200 cases per 100,000) and new hospitalizations (≥ 10 or <10 per 100,000) were our dependent variables, stratified by calendar quarter. Using logistic regression, we assessed the performance of combining wastewater metrics. RESULTS: Among 268 counties across 22 states, wastewater percentile detected high reported case and hospitalizations rates in the first quarter of 2022 (AUC 0.95 and 0.86 respectively) whereas the percent change did not (AUC 0.54 and 0.49 respectively). A wastewater percentile of 51% maximized sensitivity (0.93) and specificity (0.82) for detecting high case rates. A model inclusive of both metrics performed no better than using wastewater percentile alone. The predictive capability of wastewater percentile declined over time (AUC 0.84 and 0.72 for cases for second and third quarters of 2022). CONCLUSION: Nationwide, county wastewater levels above 51% relative to the historic peak predicted high COVID rates and hospitalization in the first quarter of 2022, but performed less well in subsequent quarters. Decline over time in predictive performance of this metric likely reflects underreporting of cases, reduced testing, and possibly lower virulence of infection due to vaccines and treatments. Cold Spring Harbor Laboratory 2023-02-08 /pmc/articles/PMC9934789/ /pubmed/36798337 http://dx.doi.org/10.1101/2023.02.06.23285542 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Varkila, Meri Montez-Rath, Maria Salomon, Joshua Yu, Xue Block, Geoffrey Owens, Douglas K. Chertow, Glenn M Parsonnet, Julie Anand, Shuchi Use of wastewater metrics to track COVID-19 in the U.S.: a national time-series analysis over the first three quarters of 2022 |
title | Use of wastewater metrics to track COVID-19 in the U.S.: a national time-series analysis over the first three quarters of 2022 |
title_full | Use of wastewater metrics to track COVID-19 in the U.S.: a national time-series analysis over the first three quarters of 2022 |
title_fullStr | Use of wastewater metrics to track COVID-19 in the U.S.: a national time-series analysis over the first three quarters of 2022 |
title_full_unstemmed | Use of wastewater metrics to track COVID-19 in the U.S.: a national time-series analysis over the first three quarters of 2022 |
title_short | Use of wastewater metrics to track COVID-19 in the U.S.: a national time-series analysis over the first three quarters of 2022 |
title_sort | use of wastewater metrics to track covid-19 in the u.s.: a national time-series analysis over the first three quarters of 2022 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9934789/ https://www.ncbi.nlm.nih.gov/pubmed/36798337 http://dx.doi.org/10.1101/2023.02.06.23285542 |
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