Detection of the Omicron BA.1 Variant of SARS-CoV-2 in Wastewater From a Las Vegas Tourist Area.

Importance: Interpretation of wastewater surveillance data is potentially confounded in communities with mobile populations, so it is important to account for this issue when conducting wastewater-based epidemiology (WBE). Objectives: To leverage spatial and temporal differences in wastewater whole-genome sequencing (WGS) data to quantify relative SARS-CoV-2 contributions from visitors to southern Nevada. Design, Setting, and Participants: This cross-sectional wastewater surveillance study was performed during the COVID-19 pandemic (March 2020 to February 2022) and included weekly influent wastewater samples that were analyzed by reverse transcription-quantitative polymerase chain reaction to quantify SARS-CoV-2 RNA and WGS for identification of variants of concern. This study was conducted in the Las Vegas, Nevada, metropolitan area, which is a semi-urban area with approximately 2.3 million residents and nearly 1 million weekly visitors. Samples were collected from 7 wastewater treatment plant (WWTP) locations that collectively serve the vast majority of southern Nevada (excluding the small number of septic systems) and 1 manhole serving the southern portion of the Las Vegas Strip. With Las Vegas tourism returning to prepandemic levels in 2021, it was hypothesized that visitors were contributing a disproportionate fraction of SARS-CoV-2 RNA to the largest WWTP in southern Nevada, potentially confounding efforts to estimate COVID-19 incidence in the local community through WBE. Main Outcomes and Measures: Relative SARS-CoV-2 load and variants from visitors vs the local population. Results: The Omicron BA.1 VOC was detected in the Las Vegas Strip manhole approximately 1 week before its detection at the WWTP locations (December 13, 2021) and by clinical testing (December 14, 2021). On December 13, Omicron-specific mutations represented a mean (SD) of 48.0% (4.2%) of all genomes from the Las Vegas Strip manhole and 4.1% (1.4%) of all genomes at facilities 2 and 3; by December 20, Omicron-specific mutations represented means (SD) of 82.0% (3.0%) of all genomes at the Las Vegas Strip manhole and 48.0% (2.8%) of all genomes at facilities 2 and 3, respectively. During this time, it was estimated that visitors contributed more than 60% of the SARS-CoV-2 load to the sewershed serving the Las Vegas Strip and that Omicron prevalence among visitors was 40% to 60% on December 13 and 80% to 100% on December 20th. Conclusions and Relevance: Wastewater surveillance is a valuable complement to clinical tools and can provide time-sensitive data for decision-makers and policy makers. This study represents a novel approach for quantifying the confounding effects of mobile populations on wastewater surveillance data, thereby allowing for modification of an existing WBE framework for estimating COVID-19 incidence in southern Nevada.

Identification and genome sequencing of an influenza H3N2 variant in wastewater from elementary schools during a surge of influenza A cases in Las Vegas, Nevada.

Real-time surveillance of infectious diseases at schools or in communities is often hampered by delays in reporting due to resource limitations and infrastructure issues. By incorporating quantitative PCR and genome sequencing, wastewater surveillance has been an effective complement to public health surveillance at the community and building-scale for pathogens such as poliovirus, SARS-CoV-2, and even the monkeypox virus. In this study, we asked whether wastewater surveillance programs at elementary schools could be leveraged to detect RNA from influenza viruses shed in wastewater. We monitored for influenza A and B viral RNA in wastewater from six elementary schools from January to May 2022. Quantitative PCR led to the identification of influenza A viral RNA at three schools, which coincided with the lifting of COVID-19 restrictions and a surge in influenza A infections in Las Vegas, Nevada, USA. We performed genome sequencing of wastewater RNA, leading to the identification of a 2021-2022 vaccine-resistant influenza A (H3N2) 3C.2a1b.2a.2 subclade. We next tested wastewater samples from a treatment plant that serviced the elementary schools, but we were unable to detect the presence of influenza A/B RNA. Together, our results demonstrate the utility of near-source wastewater surveillance for the detection of local influenza transmission in schools, which has the potential to be investigated further with paired school-level influenza incidence data.

Identification of a rare SARS-CoV-2 XL hybrid variant in wastewater and the subsequent discovery of two infected individuals in Nevada.

The identification of novel SARS-CoV-2 variants can predict new patterns of COVID-19 community transmission and lead to the deployment of public health resources. However, increased access to at-home antigen tests and reduced free PCR tests have recently led to data gaps for the surveillance of evolving SARS-CoV-2 variants. To overcome such limitations, we asked whether wastewater surveillance could be leveraged to detect rare variants circulating in a community before local detection in human cases. Here, we performed whole genome sequencing (WGS) of SARS-CoV-2 from a wastewater treatment plant serving Las Vegas, Nevada in April 2022. Using metrics that exceeded 100× depth at a coverage of >90 % of the viral genome, we identified a variant profile similar to the XL recombinant lineage containing 26 mutations found in BA.1 and BA.2 and three private mutations. Prompted by the discovery of this rare lineage in wastewater, we analyzed clinical COVID-19 sequencing data from Southern Nevada and identified two cases infected with the XL lineage. Taken together, our data highlight how wastewater genome sequencing data can be used to discover rare SARS-CoV-2 lineages in a community and complement local public health surveillance.

Urban monitoring of antimicrobial resistance during a COVID-19 surge through wastewater surveillance.

During the early phase of the COVID-19 pandemic, infected patients presented with symptoms similar to bacterial pneumonias and were treated with antibiotics before confirmation of a bacterial or fungal co-infection. We reasoned that wastewater surveillance could reveal potential relationships between reduced antimicrobial stewardship, specifically misprescribing antibiotics to treat viral infections, and the occurrence of antimicrobial resistance (AMR) in an urban community. Here, we analyzed microbial communities and AMR profiles in sewage samples from a wastewater treatment plant (WWTP) and a community shelter in Las Vegas, Nevada during a COVID-19 surge in December 2020. Using a respiratory pathogen and AMR enrichment next-generation sequencing panel, we identified four major phyla in the wastewater, including Actinobacteria, Firmicutes, Bacteroidetes and Proteobacteria. Consistent with antibiotics that were reportedly used to treat COVID-19 infections (e.g., fluoroquinolones and beta-lactams), we also measured a significant spike in corresponding AMR genes in the wastewater samples. AMR genes associated with colistin resistance (mcr genes) were also identified exclusively at the WWTP, suggesting that multidrug resistant bacterial infections were being treated during this time. We next compared the Las Vegas sewage data to local 2018-2019 antibiograms, which are antimicrobial susceptibility profile reports about common clinical pathogens. Similar to the discovery of higher levels of beta-lactamase resistance genes in sewage during 2020, beta-lactam antibiotics accounted for 51 ± 3 % of reported antibiotics used in antimicrobial susceptibility tests of 2018-2019 clinical isolates. Our data highlight how wastewater-based epidemiology (WBE) can be leveraged to complement more traditional surveillance efforts by providing community-level data to help identify current and emerging AMR threats.

Use of wastewater surveillance for early detection of Alpha and Epsilon SARS-CoV-2 variants of concern and estimation of overall COVID-19 infection burden.

A decline in diagnostic testing for SARS-CoV-2 is expected to delay the tracking of COVID-19 variants of concern and interest in the United States. We hypothesize that wastewater surveillance programs provide an effective alternative for detecting emerging variants and assessing COVID-19 incidence, particularly when clinical surveillance is limited. Here, we analyzed SARS-CoV-2 RNA in wastewater from eight locations across Southern Nevada between March 2020 and April 2021. Trends in SARS-CoV-2 RNA concentrations (ranging from 4.3 log10 gc/L to 8.7 log10 gc/L) matched trends in confirmed COVID-19 incidence, but wastewater surveillance also highlighted several limitations with the clinical data. Amplicon-based whole genome sequencing (WGS) of 86 wastewater samples identified the B.1.1.7 (Alpha) and B.1.429 (Epsilon) lineages in December 2020, but clinical sequencing failed to identify the variants until January 2021, thereby demonstrating that 'pooled' wastewater samples can sometimes expedite variant detection. Also, by calibrating fecal shedding (11.4 log10 gc/infection) and wastewater surveillance data to reported seroprevalence, we estimate that ~38% of individuals in Southern Nevada had been infected by SARS-CoV-2 as of April 2021, which is significantly higher than the 10% of individuals confirmed through clinical testing. Sewershed-specific ascertainment ratios (i.e., X-fold infection undercounts) ranged from 1.0 to 7.7, potentially due to demographic differences. Our data underscore the growing application of wastewater surveillance in not only the identification and quantification of infectious agents, but also the detection of variants of concern that may be missed when diagnostic testing is limited or unavailable.

SARS-CoV-2 variant detection at a university dormitory using wastewater genomic tools.

In the Fall of 2020, university campuses in the United States resumed on-campus instruction and implemented wastewater monitoring for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). While quantitative polymerase chain reaction (qPCR) tests were deployed successfully to detect viral RNA in wastewater across campuses, the feasibility of detecting viral variants from a residential building like a dormitory was unclear. Here, we demonstrate that wastewater surveillance from a dormitory with at least three infected students could lead to the identification of viral genomes with more than 95% coverage. Our results indicate that viral variant detection from wastewater is achievable at a dormitory and that coronavirus disease 2019 (COVID-19) wastewater surveillance programs will benefit from the implementation of viral whole genome sequencing at universities.