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Predicting COVID-19 Incidence Using Wastewater Surveillance Data, Denmark, October 2021–June 2022
Analysis of wastewater is used in many settings for surveillance of SARS-CoV-2, but it remains unclear how well wastewater testing results reflect incidence. Denmark has had an extensive wastewater analysis system that conducts 3 weekly tests in ≈200 sites and has 85% population coverage; the countr...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Centers for Disease Control and Prevention
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10370843/ https://www.ncbi.nlm.nih.gov/pubmed/37486168 http://dx.doi.org/10.3201/eid2908.221634 |
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author | McManus, Oliver Christiansen, Lasse Engbo Nauta, Maarten Krogsgaard, Lene Wulff Bahrenscheer, Naja Stolberg von Kappelgaard, Lene Christiansen, Tobias Hansen, Mikkel Hansen, Nicco Claudio Kähler, Jonas Rasmussen, Anders Richter, Stine Raith Rasmussen, Lasse Dam Franck, Kristina Træholt Ethelberg, Steen |
author_facet | McManus, Oliver Christiansen, Lasse Engbo Nauta, Maarten Krogsgaard, Lene Wulff Bahrenscheer, Naja Stolberg von Kappelgaard, Lene Christiansen, Tobias Hansen, Mikkel Hansen, Nicco Claudio Kähler, Jonas Rasmussen, Anders Richter, Stine Raith Rasmussen, Lasse Dam Franck, Kristina Træholt Ethelberg, Steen |
author_sort | McManus, Oliver |
collection | PubMed |
description | Analysis of wastewater is used in many settings for surveillance of SARS-CoV-2, but it remains unclear how well wastewater testing results reflect incidence. Denmark has had an extensive wastewater analysis system that conducts 3 weekly tests in ≈200 sites and has 85% population coverage; the country also offers free SARS-CoV-2 PCR tests to all residents. Using time series analysis for modeling, we found that wastewater data, combined with information on circulating variants and the number of human tests performed, closely fitted the incidence curve of persons testing positive. The results were consistent at a regional level and among a subpopulation of frequently tested healthcare personnel. We used wastewater analysis data to estimate incidence after testing was reduced to a minimum after March 2022. These results imply that data from a large-scale wastewater surveillance system can serve as a good proxy for COVID-19 incidence and for epidemic control. |
format | Online Article Text |
id | pubmed-10370843 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Centers for Disease Control and Prevention |
record_format | MEDLINE/PubMed |
spelling | pubmed-103708432023-08-01 Predicting COVID-19 Incidence Using Wastewater Surveillance Data, Denmark, October 2021–June 2022 McManus, Oliver Christiansen, Lasse Engbo Nauta, Maarten Krogsgaard, Lene Wulff Bahrenscheer, Naja Stolberg von Kappelgaard, Lene Christiansen, Tobias Hansen, Mikkel Hansen, Nicco Claudio Kähler, Jonas Rasmussen, Anders Richter, Stine Raith Rasmussen, Lasse Dam Franck, Kristina Træholt Ethelberg, Steen Emerg Infect Dis Research Analysis of wastewater is used in many settings for surveillance of SARS-CoV-2, but it remains unclear how well wastewater testing results reflect incidence. Denmark has had an extensive wastewater analysis system that conducts 3 weekly tests in ≈200 sites and has 85% population coverage; the country also offers free SARS-CoV-2 PCR tests to all residents. Using time series analysis for modeling, we found that wastewater data, combined with information on circulating variants and the number of human tests performed, closely fitted the incidence curve of persons testing positive. The results were consistent at a regional level and among a subpopulation of frequently tested healthcare personnel. We used wastewater analysis data to estimate incidence after testing was reduced to a minimum after March 2022. These results imply that data from a large-scale wastewater surveillance system can serve as a good proxy for COVID-19 incidence and for epidemic control. Centers for Disease Control and Prevention 2023-08 /pmc/articles/PMC10370843/ /pubmed/37486168 http://dx.doi.org/10.3201/eid2908.221634 Text en https://creativecommons.org/licenses/by/4.0/Emerging Infectious Diseases is a publication of the U.S. Government. This publication is in the public domain and is therefore without copyright. All text from this work may be reprinted freely. Use of these materials should be properly cited. |
spellingShingle | Research McManus, Oliver Christiansen, Lasse Engbo Nauta, Maarten Krogsgaard, Lene Wulff Bahrenscheer, Naja Stolberg von Kappelgaard, Lene Christiansen, Tobias Hansen, Mikkel Hansen, Nicco Claudio Kähler, Jonas Rasmussen, Anders Richter, Stine Raith Rasmussen, Lasse Dam Franck, Kristina Træholt Ethelberg, Steen Predicting COVID-19 Incidence Using Wastewater Surveillance Data, Denmark, October 2021–June 2022 |
title | Predicting COVID-19 Incidence Using Wastewater Surveillance Data, Denmark, October 2021–June 2022 |
title_full | Predicting COVID-19 Incidence Using Wastewater Surveillance Data, Denmark, October 2021–June 2022 |
title_fullStr | Predicting COVID-19 Incidence Using Wastewater Surveillance Data, Denmark, October 2021–June 2022 |
title_full_unstemmed | Predicting COVID-19 Incidence Using Wastewater Surveillance Data, Denmark, October 2021–June 2022 |
title_short | Predicting COVID-19 Incidence Using Wastewater Surveillance Data, Denmark, October 2021–June 2022 |
title_sort | predicting covid-19 incidence using wastewater surveillance data, denmark, october 2021–june 2022 |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10370843/ https://www.ncbi.nlm.nih.gov/pubmed/37486168 http://dx.doi.org/10.3201/eid2908.221634 |
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