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Wastewater-based epidemiology predicts COVID-19-induced weekly new hospital admissions in over 150 USA counties
Although the coronavirus disease (COVID-19) emergency status is easing, the COVID-19 pandemic continues to affect healthcare systems globally. It is crucial to have a reliable and population-wide prediction tool for estimating COVID-19-induced hospital admissions. We evaluated the feasibility of usi...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10382499/ https://www.ncbi.nlm.nih.gov/pubmed/37507407 http://dx.doi.org/10.1038/s41467-023-40305-x |
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author | Li, Xuan Liu, Huan Gao, Li Sherchan, Samendra P. Zhou, Ting Khan, Stuart J. van Loosdrecht, Mark C. M. Wang, Qilin |
author_facet | Li, Xuan Liu, Huan Gao, Li Sherchan, Samendra P. Zhou, Ting Khan, Stuart J. van Loosdrecht, Mark C. M. Wang, Qilin |
author_sort | Li, Xuan |
collection | PubMed |
description | Although the coronavirus disease (COVID-19) emergency status is easing, the COVID-19 pandemic continues to affect healthcare systems globally. It is crucial to have a reliable and population-wide prediction tool for estimating COVID-19-induced hospital admissions. We evaluated the feasibility of using wastewater-based epidemiology (WBE) to predict COVID-19-induced weekly new hospitalizations in 159 counties across 45 states in the United States of America (USA), covering a population of nearly 100 million. Using county-level weekly wastewater surveillance data (over 20 months), WBE-based models were established through the random forest algorithm. WBE-based models accurately predicted the county-level weekly new admissions, allowing a preparation window of 1-4 weeks. In real applications, periodically updated WBE-based models showed good accuracy and transferability, with mean absolute error within 4-6 patients/100k population for upcoming weekly new hospitalization numbers. Our study demonstrated the potential of using WBE as an effective method to provide early warnings for healthcare systems. |
format | Online Article Text |
id | pubmed-10382499 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103824992023-07-30 Wastewater-based epidemiology predicts COVID-19-induced weekly new hospital admissions in over 150 USA counties Li, Xuan Liu, Huan Gao, Li Sherchan, Samendra P. Zhou, Ting Khan, Stuart J. van Loosdrecht, Mark C. M. Wang, Qilin Nat Commun Article Although the coronavirus disease (COVID-19) emergency status is easing, the COVID-19 pandemic continues to affect healthcare systems globally. It is crucial to have a reliable and population-wide prediction tool for estimating COVID-19-induced hospital admissions. We evaluated the feasibility of using wastewater-based epidemiology (WBE) to predict COVID-19-induced weekly new hospitalizations in 159 counties across 45 states in the United States of America (USA), covering a population of nearly 100 million. Using county-level weekly wastewater surveillance data (over 20 months), WBE-based models were established through the random forest algorithm. WBE-based models accurately predicted the county-level weekly new admissions, allowing a preparation window of 1-4 weeks. In real applications, periodically updated WBE-based models showed good accuracy and transferability, with mean absolute error within 4-6 patients/100k population for upcoming weekly new hospitalization numbers. Our study demonstrated the potential of using WBE as an effective method to provide early warnings for healthcare systems. Nature Publishing Group UK 2023-07-28 /pmc/articles/PMC10382499/ /pubmed/37507407 http://dx.doi.org/10.1038/s41467-023-40305-x Text en © The Author(s) 2023 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 Li, Xuan Liu, Huan Gao, Li Sherchan, Samendra P. Zhou, Ting Khan, Stuart J. van Loosdrecht, Mark C. M. Wang, Qilin Wastewater-based epidemiology predicts COVID-19-induced weekly new hospital admissions in over 150 USA counties |
title | Wastewater-based epidemiology predicts COVID-19-induced weekly new hospital admissions in over 150 USA counties |
title_full | Wastewater-based epidemiology predicts COVID-19-induced weekly new hospital admissions in over 150 USA counties |
title_fullStr | Wastewater-based epidemiology predicts COVID-19-induced weekly new hospital admissions in over 150 USA counties |
title_full_unstemmed | Wastewater-based epidemiology predicts COVID-19-induced weekly new hospital admissions in over 150 USA counties |
title_short | Wastewater-based epidemiology predicts COVID-19-induced weekly new hospital admissions in over 150 USA counties |
title_sort | wastewater-based epidemiology predicts covid-19-induced weekly new hospital admissions in over 150 usa counties |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10382499/ https://www.ncbi.nlm.nih.gov/pubmed/37507407 http://dx.doi.org/10.1038/s41467-023-40305-x |
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