Predicting daily COVID-19 case rates from SARS-CoV-2 RNA concentrations across a diversity of wastewater catchments
Predicting daily COVID-19 case rates from SARS-CoV-2 RNA concentrations across a diversity of wastewater catchments
Abstract We assessed the relationship between municipality COVID-19 case rates and SARS-CoV-2 concentrations in the primary sludge of corresponding wastewater treatment facilities. Over 1,000 daily primary sludge samples were collected from six wastewater treatment facilities with catchments serving 18 cities and towns in the State of Connecticut, USA. Samples were analyzed for SARS-CoV-2 RNA concentrations during a six-month time period that overlapped with fall 2020 and winter 2021 COVID-19 outbreaks in each municipality. We fit a single regression model to estimate reported case rates in the six municipalities from SARS-CoV-2 RNA concentrations collected daily from corresponding wastewater treatment facilities. Results demonstrate the ability of SARS-CoV-2 RNA concentrations in primary sludge to estimate COVID-19 reported case rates across treatment facilities and wastewater catchments, with coverage probabilities ranging from 0.94 to 0.96. Leave-one-out cross validation suggests that the model can be broadly applied to wastewater catchments that range in more than one order of magnitude in population served. Estimation of case rates from wastewater data can be useful in locations with limited testing availability or testing disparities, or delays in individual COVID-19 testing programs.
Kaplan Edward H.、Cartter Matthew、Ko Albert I.、Cozens Duncan、Brackney Doug E.、Crawford Forrest W.、Pan Annabelle、Peccia Jordan、Zulli Alessandro、Sanchez Marcela、Bart Stephen M.
Department of Chemical and Environmental Engineering, School of Engineering and Applied Science, Yale University||Yale School of Management, Yale University||Yale School of Public Health, Yale UniversityConnecticut Department of Public Health||Yale School of Public Health, Yale UniversityDepartment of Epidemiology of Microbial Disease, Yale School of Public Health, Yale UniversityConnecticut Agricultural Experimental Station, State of ConnecticutYale School of Public Health, Yale University||Connecticut Agricultural Experimental Station, State of ConnecticutDepartment of Biostatistics, Yale School of Public Health, Yale University||Department of Statistics and Data Science, Yale University||Department of Ecology and Evolutionary Biology, Yale University||Yale School of Management, Yale UniversityDepartment of Chemical and Environmental Engineering, School of Engineering and Applied Science, Yale UniversityDepartment of Chemical and Environmental Engineering, School of Engineering and Applied Science, Yale UniversityDepartment of Chemical and Environmental Engineering, School of Engineering and Applied Science, Yale UniversityDepartment of Chemical and Environmental Engineering, School of Engineering and Applied Science, Yale UniversityEpidemic Intelligence Service, Centers for Disease Control and Prevention||Connecticut Department of Public Health
医药卫生理论医学研究方法预防医学
SARS-CoV-2wastewater-based epidemiologyprimary sludgeregression analysiscase rate estimationquantitative PCR
Kaplan Edward H.,Cartter Matthew,Ko Albert I.,Cozens Duncan,Brackney Doug E.,Crawford Forrest W.,Pan Annabelle,Peccia Jordan,Zulli Alessandro,Sanchez Marcela,Bart Stephen M..Predicting daily COVID-19 case rates from SARS-CoV-2 RNA concentrations across a diversity of wastewater catchments[EB/OL].(2025-03-28)[2025-04-28].https://www.medrxiv.org/content/10.1101/2021.04.27.21256140.点此复制
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