Wastewater genomic surveillance captures early detection of Omicron in Utah

Wastewater-based epidemiology has emerged as a powerful public health tool to trace new outbreaks, detect trends in infection and provide an early warning of COVID-19 community spread. Here, we investigated the spread of SARS-CoV-2 infections across Utah by characterizing lineages and mutations detected in wastewater samples. We sequenced over 1,200 samples from 32 sewersheds collected between November 2021 and March 2022. Wastewater sequencing confirmed the presence of Omicron (B.1.1.529) in Utah in samples collected on November 19, 2021, up to ten days before its corresponding detection via clinical sequencing. Analysis of diversity of SARS-CoV-2 lineages revealed Delta as the most frequently detected lineage during November, 2021 (67.71%), but it started declining in December, 2021 with the onset of Omicron (B.1.1529) and its sub-lineage BA.1 (6.79%). Proportion of Omicron increased to ∼58% by January 4th 2022 and completely displaced Delta by February 7th, 2022. Wastewater genomic surveillance revealed the presence of Omicron sub-lineage BA.3, a lineage that is yet to be identified from Utah’s clinical surveillance. Interestingly, several Omicron-defining mutations began to appear in early November, 2021 and increased in prevalence across sewersheds from December to January. Our study suggests that tracking epidemiologically relevant mutations is critical in detecting emerging lineages in the early stages of an outbreak. Wastewater genomic epidemiology provides an unbiased representation of community-wide infection dynamics and is an excellent complementary tool to SARS-CoV-2 clinical surveillance, with the potential of guiding public health action and policy decisions. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was supported by the Centers for Disease Control and Prevention(CDC) Epidemiology and Laboratory Capacity for Prevention and Control of Emerging Infectious Diseases (ELC) Enhanced Detection Cooperative Agreement. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes The sequence data generated in the present study has been submitted to NCBI Sequence Read Archive and available under BioProject PRJNA812604.