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Prediction of COVID-19 positive cases, a nation-wide SARS-CoV-2 wastewater-based epidemiology study
Taking advantage of Estonia's small size and population, we have employed wastewater-based epidemiology approach to monitor the spread of SARS-CoV-2, releasing weekly nation-wide updates. In this study we report results obtained between August 2020 and December 2021. Weekly 24 h composite sampl...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Published by Elsevier Ltd.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9845016/ https://www.ncbi.nlm.nih.gov/pubmed/36682239 http://dx.doi.org/10.1016/j.watres.2023.119617 |
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author | Kisand, Veljo Laas, Peeter Palmik-Das, Kadi Panksep, Kristel Tammert, Helen Albreht, Leena Allemann, Hille Liepkalns, Lauri Vooro, Katri Ritz, Christian Hauryliuk, Vasili Tenson, Tanel |
author_facet | Kisand, Veljo Laas, Peeter Palmik-Das, Kadi Panksep, Kristel Tammert, Helen Albreht, Leena Allemann, Hille Liepkalns, Lauri Vooro, Katri Ritz, Christian Hauryliuk, Vasili Tenson, Tanel |
author_sort | Kisand, Veljo |
collection | PubMed |
description | Taking advantage of Estonia's small size and population, we have employed wastewater-based epidemiology approach to monitor the spread of SARS-CoV-2, releasing weekly nation-wide updates. In this study we report results obtained between August 2020 and December 2021. Weekly 24 h composite samples were collected from wastewater treatment plants of larger towns already covered 65% of the total population that was complemented up to 40 additional grab samples from smaller towns/villages and the specific sites of concern. The N3 gene abundance was quantified by RT-qPCR. The N3 gene copy number (concentration) in wastewater fluctuated in accordance with the SARS-CoV-2 spread within the total population, with N3 abundance starting to increase 1.25 weeks (9 days) (95% CI: [1.10, 1.41]) before a rise in COVID-19 positive cases. Statistical model between the load of virus in wastewater and number of infected people validated with the Alpha variant wave (B.1.1.17) could be used to predict the order of magnitude in incidence numbers in Delta wave (B.1.617.2) in fall 2021. Targeted testing of student dormitories, retirement and nursing homes and prisons resulted in successful early discovery of outbreaks. We put forward a SARS-CoV-2 Wastewater Index (SARS2-WI) indicator of normalized virus load as COVID-19 infection metric to complement the other metrics currently used in disease control and prevention: dynamics of effective reproduction number (Re), 7-day mean of new cases, and a sum of new cases within last 14 days. In conclusion, an efficient surveillance system that combines analysis of composite and grab samples was established in Estonia. There is considerable discussion how the viral load in wastewater correlates with the number of infected people. Here we show that this correlation can be found. Moreover, we confirm that an increased signal in wastewater is observed before the increase in the number of infections. The surveillance system helped to inform public health policy and place direct interventions during the COVID-19 pandemic in Estonia via early warning of epidemic spread in various regions of the country. |
format | Online Article Text |
id | pubmed-9845016 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98450162023-01-18 Prediction of COVID-19 positive cases, a nation-wide SARS-CoV-2 wastewater-based epidemiology study Kisand, Veljo Laas, Peeter Palmik-Das, Kadi Panksep, Kristel Tammert, Helen Albreht, Leena Allemann, Hille Liepkalns, Lauri Vooro, Katri Ritz, Christian Hauryliuk, Vasili Tenson, Tanel Water Res Article Taking advantage of Estonia's small size and population, we have employed wastewater-based epidemiology approach to monitor the spread of SARS-CoV-2, releasing weekly nation-wide updates. In this study we report results obtained between August 2020 and December 2021. Weekly 24 h composite samples were collected from wastewater treatment plants of larger towns already covered 65% of the total population that was complemented up to 40 additional grab samples from smaller towns/villages and the specific sites of concern. The N3 gene abundance was quantified by RT-qPCR. The N3 gene copy number (concentration) in wastewater fluctuated in accordance with the SARS-CoV-2 spread within the total population, with N3 abundance starting to increase 1.25 weeks (9 days) (95% CI: [1.10, 1.41]) before a rise in COVID-19 positive cases. Statistical model between the load of virus in wastewater and number of infected people validated with the Alpha variant wave (B.1.1.17) could be used to predict the order of magnitude in incidence numbers in Delta wave (B.1.617.2) in fall 2021. Targeted testing of student dormitories, retirement and nursing homes and prisons resulted in successful early discovery of outbreaks. We put forward a SARS-CoV-2 Wastewater Index (SARS2-WI) indicator of normalized virus load as COVID-19 infection metric to complement the other metrics currently used in disease control and prevention: dynamics of effective reproduction number (Re), 7-day mean of new cases, and a sum of new cases within last 14 days. In conclusion, an efficient surveillance system that combines analysis of composite and grab samples was established in Estonia. There is considerable discussion how the viral load in wastewater correlates with the number of infected people. Here we show that this correlation can be found. Moreover, we confirm that an increased signal in wastewater is observed before the increase in the number of infections. The surveillance system helped to inform public health policy and place direct interventions during the COVID-19 pandemic in Estonia via early warning of epidemic spread in various regions of the country. Published by Elsevier Ltd. 2023-03-01 2023-01-18 /pmc/articles/PMC9845016/ /pubmed/36682239 http://dx.doi.org/10.1016/j.watres.2023.119617 Text en © 2023 Published by Elsevier Ltd. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Kisand, Veljo Laas, Peeter Palmik-Das, Kadi Panksep, Kristel Tammert, Helen Albreht, Leena Allemann, Hille Liepkalns, Lauri Vooro, Katri Ritz, Christian Hauryliuk, Vasili Tenson, Tanel Prediction of COVID-19 positive cases, a nation-wide SARS-CoV-2 wastewater-based epidemiology study |
title | Prediction of COVID-19 positive cases, a nation-wide SARS-CoV-2 wastewater-based epidemiology study |
title_full | Prediction of COVID-19 positive cases, a nation-wide SARS-CoV-2 wastewater-based epidemiology study |
title_fullStr | Prediction of COVID-19 positive cases, a nation-wide SARS-CoV-2 wastewater-based epidemiology study |
title_full_unstemmed | Prediction of COVID-19 positive cases, a nation-wide SARS-CoV-2 wastewater-based epidemiology study |
title_short | Prediction of COVID-19 positive cases, a nation-wide SARS-CoV-2 wastewater-based epidemiology study |
title_sort | prediction of covid-19 positive cases, a nation-wide sars-cov-2 wastewater-based epidemiology study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9845016/ https://www.ncbi.nlm.nih.gov/pubmed/36682239 http://dx.doi.org/10.1016/j.watres.2023.119617 |
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