Measurement of SARS-CoV-2 RNA in wastewater tracks community infection dynamics

被引:0
作者
Jordan Peccia
Alessandro Zulli
Doug E. Brackney
Nathan D. Grubaugh
Edward H. Kaplan
Arnau Casanovas-Massana
Albert I. Ko
Amyn A. Malik
Dennis Wang
Mike Wang
Joshua L. Warren
Daniel M. Weinberger
Wyatt Arnold
Saad B. Omer
机构
[1] Yale University,Department of Chemical and Environmental Engineering, School of Engineering and Applied Science
[2] State of Connecticut,Connecticut Agricultural Experimental Station
[3] Yale University,Department of Epidemiology of Microbial Disease, School of Public Health
[4] Yale School of Public Health,Public Health Modeling
[5] Yale University,School of Management
[6] Yale School of Medicine,Department of Biostatistics, Yale School of Public Health
[7] Yale Institute for Global Health,undefined
[8] Yale University,undefined
[9] Yale School of Nursing,undefined
来源
Nature Biotechnology | 2020年 / 38卷
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摘要
We measured severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in primary sewage sludge in the New Haven, Connecticut, USA, metropolitan area during the Coronavirus Disease 2019 (COVID-19) outbreak in Spring 2020. SARS-CoV-2 RNA was detected throughout the more than 10-week study and, when adjusted for time lags, tracked the rise and fall of cases seen in SARS-CoV-2 clinical test results and local COVID-19 hospital admissions. Relative to these indicators, SARS-CoV-2 RNA concentrations in sludge were 0–2 d ahead of SARS-CoV-2 positive test results by date of specimen collection, 0–2 d ahead of the percentage of positive tests by date of specimen collection, 1–4 d ahead of local hospital admissions and 6–8 d ahead of SARS-CoV-2 positive test results by reporting date. Our data show the utility of viral RNA monitoring in municipal wastewater for SARS-CoV-2 infection surveillance at a population-wide level. In communities facing a delay between specimen collection and the reporting of test results, immediate wastewater results can provide considerable advance notice of infection dynamics.
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页码:1164 / 1167
页数:3
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