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Scaling SARS-CoV-2 wastewater concentrations to population estimates of infection.
Kaplan, Edward H; Zulli, Alessandro; Sanchez, Marcela; Peccia, Jordan.
  • Kaplan EH; Yale School of Management, Yale University, New Haven, CT, 06520, USA. edward.kaplan@yale.edu.
  • Zulli A; Yale School of Public Health, Yale University, New Haven, CT, 06520, USA. edward.kaplan@yale.edu.
  • Sanchez M; Department of Chemical and Environmental Engineering, School of Engineering and Applied Science, Yale University, New Haven, CT, 06520, USA. edward.kaplan@yale.edu.
  • Peccia J; Department of Chemical and Environmental Engineering, School of Engineering and Applied Science, Yale University, New Haven, CT, 06520, USA.
Sci Rep ; 12(1): 3487, 2022 03 03.
Article in English | MEDLINE | ID: covidwho-1730315
ABSTRACT
Monitoring the progression of SARS-CoV-2 outbreaks requires accurate estimation of the unobservable fraction of the population infected over time in addition to the observed numbers of COVID-19 cases, as the latter present a distorted view of the pandemic due to changes in test frequency and coverage over time. The objective of this report is to describe and illustrate an approach that produces representative estimates of the unobservable cumulative incidence of infection by scaling the daily concentrations of SARS-CoV-2 RNA in wastewater from the consistent population contribution of fecal material to the sewage collection system.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Wastewater / SARS-CoV-2 / COVID-19 Type of study: Observational study Limits: Humans Language: English Journal: Sci Rep Year: 2022 Document Type: Article Affiliation country: S41598-022-07523-7

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Wastewater / SARS-CoV-2 / COVID-19 Type of study: Observational study Limits: Humans Language: English Journal: Sci Rep Year: 2022 Document Type: Article Affiliation country: S41598-022-07523-7