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- W4226142177 abstract "Abstract Wastewater based epidemiology (WBE) has emerged as a strategy to identify, locate, and manage outbreaks of COVID19, and thereby possibly prevent surges in cases, which overwhelm local to global health care networks. The WBE process is based on assaying municipal wastewater for molecular markers of the SARS-CoV-2 virus. The standard process for sampling municipal wastewater is both time-consuming and requires the handling of large quantities of wastewater, which negatively affect throughput and timely reporting, and can increase safety risks. We report on a method to assay multiple sub-samples of a bulk wastewater sample. We document the effectiveness of this new approach by way of comparison of technologies for automating RNA purification from wastewater samples. We compared processes using the Perkin-Elmer Chemagic™ 360 to a PEG/NaCl/Qiagen protocol that is used for detection of N1 and N2 SARS-CoV-2 markers by the majority of 19 pandemic wastewater testing labs in the State of Michigan. Specifically, we found that the Chemagic™ 360 lowered handling time, decreased the amount of wastewater required by 10-fold, increased the amount of RNA isolated per µl of final elution product by approximately five-fold, and had no deleterious effect on subsequent ddPCR analysis. Moreover, for detection of markers on the borderline of detectability, we found that use of the Chemagic™ 360 enabled the detection of viral markers in a significant number of samples for which the result with the PEG/NaCl/Qiagen method was below the level of detectability. This improvement in detectability of the viral markers might be particularly important for early warning to public health authorities at the beginning of an outbreak." @default.
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- W4226142177 date "2022-04-05" @default.
- W4226142177 modified "2023-10-16" @default.
- W4226142177 title "Automated method to extract and purify RNA from wastewater enables more sensitive detection of SARS-CoV-2 markers in community sewersheds" @default.
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- W4226142177 doi "https://doi.org/10.1101/2022.04.03.22273370" @default.
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