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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.
Affiliation
  • Kisand V; Institute of Technology, University of Tartu, Estonia. Electronic address: kisand@ut.ee.
  • Laas P; Institute of Technology, University of Tartu, Estonia.
  • Palmik-Das K; Institute of Technology, University of Tartu, Estonia.
  • Panksep K; Institute of Technology, University of Tartu, Estonia.
  • Tammert H; Institute of Technology, University of Tartu, Estonia.
  • Albreht L; Estonian Health Board, Tallinn, Estonia.
  • Allemann H; Estonian Environmental Research Centre, Tallinn, Estonia.
  • Liepkalns L; Estonian Health Board, Tallinn, Estonia.
  • Vooro K; Estonian Environmental Research Centre, Tallinn, Estonia.
  • Ritz C; Department of Population Health and Morbidity, National Institute of Public Health, University of Southern Denmark, Denmark.
  • Hauryliuk V; Institute of Technology, University of Tartu, Estonia; Department of Experimental Medical Science, Lund University, Sweden.
  • Tenson T; Institute of Technology, University of Tartu, Estonia. Electronic address: tanel.tenson@ut.ee.
Water Res ; 231: 119617, 2023 Mar 01.
Article de En | MEDLINE | ID: mdl-36682239
ABSTRACT
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.
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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: SARS-CoV-2 / COVID-19 Type d'étude: Prognostic_studies / Risk_factors_studies / Screening_studies Limites: Humans Langue: En Journal: Water Res Année: 2023 Type de document: Article

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: SARS-CoV-2 / COVID-19 Type d'étude: Prognostic_studies / Risk_factors_studies / Screening_studies Limites: Humans Langue: En Journal: Water Res Année: 2023 Type de document: Article