Enhanced Detection of Recently Emerged SARS-CoV-2 Variants of Concern in Wastewater

SARS-CoV-2 RNA shedding in stool enabled wastewater surveillance for the genetic material of the virus. With the emergence of novel variants of concern and interest it becomes increasingly important to track arrival and spread of these variants. However, most current approaches rely on the manually curated lists of mutations phenotypically associated with the variants of concern. The resulting data has many overlaps between distinct variants leading to less specific characterization of complex sample mixtures that result from wastewater monitoring. In our work we propose a simple and specific method for characterization of wastewater samples by introducing the concept of quasi-unique mutations. Our approach is data driven and results in earlier detection and higher resolution of variants of concern emergence patterns in wastewater data.