Biology

Enabling accurate and early detection of recently emerged SARS-CoV-2 variants of concern in wastewater

N. Sapoval, Y. Liu, et al.

Discover QualD, a groundbreaking bioinformatics tool designed to detect SARS-CoV-2 variants in wastewater, offering faster detection up to three weeks earlier and exceptional accuracy over 95%. Developed by Nicolae Sapoval, Yunxi Liu, Esther G. Lou, Loren Hopkins, Katherine B. Ensor, Rebecca Schneider, Lauren B. Stadler, and Todd J. Treangen, QualD outperforms traditional tools, setting a new standard in public health monitoring.

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Abstract

As clinical testing declines, wastewater monitoring can provide crucial surveillance on the emergence of SARS-CoV-2 variant of concerns (VoCs) in communities. In this paper we present QualD, a novel bioinformatics tool for VoC detection based on quasi-unique mutations. The benefits of QualD are three-fold: (i) provides up to 3-week earlier VoC detection, (ii) accurate VoC detection (>95% precision on simulated benchmarks), and (iii) leverages all mutational signatures (including insertions & deletions).

Publisher

Nature Communications

Published On

May 17, 2023

Authors

Nicolae Sapoval, Yunxi Liu, Esther G. Lou, Loren Hopkins, Katherine B. Ensor, Rebecca Schneider, Lauren B. Stadler, Todd J. Treangen

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