RESUMO
Background: Most seasonally circulating enteroviruses result in asymptomatic or mildly symptomatic infections. In rare cases, however, infection with some subtypes can result in paralysis or death. Of the 300 subtypes known, only poliovirus is reportable, limiting our understanding of the distribution of other enteroviruses that can cause clinical disease. Objective: The overarching objectives of this study were to: 1) describe the distribution of enteroviruses in Arizona during the late summer and fall of 2022, the time of year when they are thought to be most abundant, and 2) demonstrate the utility of viral pan-assay approaches for semi-agnostic discovery that can be followed up by more targeted assays and phylogenomics. Methods: This study utilizes pooled nasal samples collected from school-aged children and long-term care facility residents, and wastewater from multiple locations in Arizona during July-October of 2022. We used PCR to amplify and sequence a region common to all enteroviruses, followed by species-level bioinformatic characterization using the QIIME 2 platform. For Enterovirus-D68 (EV-D68), detection was carried out using RT-qPCR, followed by confirmation using near-complete whole EV-D68 genome sequencing using a newly designed tiled amplicon approach. Results: In the late summer and early fall of 2022, multiple enterovirus species were identified in Arizona wastewater, with Coxsackievirus A6, EV-D68, and Coxsackievirus A19 composing 86% of the characterized reads sequenced. While EV-D68 was not identified in pooled human nasal samples, and the only reported acute flaccid myelitis case in Arizona did not test positive for the virus, an in-depth analysis of EV-D68 in wastewater revealed that the virus was circulating from August through mid-October. A phylogenetic analysis on this relatively limited dataset revealed just a few importations into the state, with a single clade indicating local circulation. Significance: This study further supports the utility of wastewater-based epidemiology to identify potential public health threats. Our further investigations into EV-D68 shows how these data might help inform healthcare diagnoses for children presenting with concerning neurological symptoms.
RESUMO
Genomic surveillance and wastewater tracking strategies were used to strengthen the public health response to an outbreak of the SARS-CoV-2 Delta AY.25 lineage associated with a university campus in Arizona. Epidemiologic and clinical data routinely gathered through contact tracing were matched to SARS-CoV-2 genomes belonging to an outbreak of AY.25 identified through ongoing phylogenomic analyses. Continued phylogenetic analyses were conducted to further describe the AY.25 outbreak. Wastewater collected twice weekly from sites across campus was tested for SARS-CoV-2 by RT-qPCR, and subsequently sequenced to identify variants. The AY.25 outbreak was defined by a single mutation (C18804T) and comprised 379 genomes from SARS-CoV-2 positive cases associated with the university and community. Several undergraduate student gatherings and congregate living settings on campus likely contributed to the rapid spread of COVID-19 across the university with secondary transmission into the community. The clade defining mutation was also found in wastewater samples collected from around student dormitories a week before the semester began, and 9 days before cases were identified. Genomic, epidemiologic, and wastewater surveillance provided evidence that an AY.25 clone was likely imported into the university setting just prior to the onset of the Fall 2021 semester, rapidly spread through a subset of the student population, and then subsequent spillover occurred in the surrounding community. The university and local public health department worked closely together to facilitate timely reporting of cases, identification of close contacts, and other necessary response and mitigation strategies. The emergence of new SARS-CoV-2 variants and potential threat of other infectious disease outbreaks on university campuses presents an opportunity for future comprehensive One Health genomic data driven, targeted interventions.
