Direct detection of canine picornavirus complete coding sequence in wastewater using long-range reverse-transcriptase polymerase chain reaction and long-read sequencing.

We describe four complete coding sequence (cCDS) of canine picornavirus from wastewater in Arizona, USA detected by coupling cCDS single-contig (∼7.5 kb) reverse-transcriptase polymerase chain reaction (RT-PCR) and low-cost long-read high-throughput sequencing. For viruses of medical/veterinary importance, this workflow expands possibilities of wastewater based genomic epidemiology for exploring virus evolutionary dynamics especially in low-resource settings.

Rhizobium Phage-Like Microvirus Genome Sequence Identified in Wastewater in Arizona, USA, in November 2020 Encodes an Endolysin and a Putative Multiheme Cytochrome c-like Protein.

We describe the genome (4,696 nucleotides [GC content, 56%; coverage, 3,641×) of MAZ-Nov-2020, a microvirus identified from municipal wastewater in Maricopa County, Arizona, USA, in November 2020. The MAZ-Nov-2020 genome encodes major capsid protein, endolysin, replication initiator protein, and two hypothetical proteins, one of which was predicted to likely be a membrane-associated multiheme cytochrome c.

Leveraging an established neighbourhood-level, open access wastewater monitoring network to address public health priorities: a population-based study.

BACKGROUND: Before the COVID-19 pandemic, the US opioid epidemic triggered a collaborative municipal and academic effort in Tempe, Arizona, which resulted in the world's first open access dashboard featuring neighbourhood-level trends informed by wastewater-based epidemiology (WBE). This study aimed to showcase how wastewater monitoring, once established and accepted by a community, could readily be adapted to respond to newly emerging public health priorities. METHODS: In this population-based study in Greater Tempe, Arizona, an existing opioid monitoring WBE network was modified to track SARS-CoV-2 transmission through the analysis of 11 contiguous wastewater catchments. Flow-weighted and time-weighted 24 h composite samples of untreated wastewater were collected at each sampling location within the wastewater collection system for 3 days each week (Tuesday, Thursday, and Saturday) from April 1, 2020, to March 31, 2021 (Area 7 and Tempe St Luke's Hospital were added in July, 2020). Reverse transcription quantitative PCR targeting the E gene of SARS-CoV-2 isolated from the wastewater samples was used to determine the number of genome copies in each catchment. Newly detected clinical cases of COVID-19 by zip code within the City of Tempe, Arizona were reported daily by the Arizona Department of Health Services from May 23, 2020. Maricopa County-level new positive cases, COVID-19-related hospitalisations, deaths, and long-term care facility deaths per day are publicly available and were collected from the Maricopa County Epidemic Curve Dashboard. Viral loads of SARS-CoV-2 (genome copies per day) measured in wastewater from each catchment were aggregated at the zip code level and city level and compared with the clinically reported data using root mean square error to investigate early warning capability of WBE. FINDINGS: Between April 1, 2020, and March 31, 2021, 1556 wastewater samples were analysed. Most locations showed two waves in viral levels peaking in June, 2020, and December, 2020-January, 2021. An additional wave of viral load was seen in catchments close to Arizona State University (Areas 6 and 7) at the beginning of the fall (autumn) semester in late August, 2020. Additionally, an early infection hotspot was detected in the Town of Guadalupe, Arizona, starting the week of May 4, 2020, that was successfully mitigated through targeted interventions. A shift in early warning potential of WBE was seen, from a leading (mean of 8·5 days [SD 2·1], June, 2020) to a lagging (-2·0 days [1·4], January, 2021) indicator compared with newly reported clinical cases. INTERPRETATION: Lessons learned from leveraging an existing neighbourhood-level WBE reporting dashboard include: (1) community buy-in is key, (2) public data sharing is effective, and (3) sub-ZIP-code (postal code) data can help to pinpoint populations at risk, track intervention success in real time, and reveal the effect of local clinical testing capacity on WBE's early warning capability. This successful demonstration of transitioning WBE efforts from opioids to COVID-19 encourages an expansion of WBE to tackle newly emerging and re-emerging threats (eg, mpox and polio). FUNDING: National Institutes of Health's RADx-rad initiative, National Science Foundation, Virginia G Piper Charitable Trust, J M Kaplan Fund, and The Flinn Foundation.

Canine Parvovirus 2C Identified in Dog Feces from Poop Bags Collected from Outdoor Waste Bins in Arizona USA, June 2022.

Canine parvoviruses (CPVs) are a major cause of morbidity and mortality in dogs. However, surveillance has been largely limited to clinically manifest cases, resulting in a dearth of CPV genomic information on virus type, abundance, and diversity, limiting our understanding of its evolutionary dynamics. We tested the feasibility of using dog feces in poop bags collected from outdoor waste bins as a source for environmental surveillance of CPV. After polymerase chain reaction, long-read sequencing, and bioinformatics, we identified that CPV-2c was present in Arizona, USA, in June 2022 and documented variants with amino acid substitutions 530E and 101K in NS1 and NS2, respectively. Based on publicly available sequence data in GenBank as of January 2023, the CPV genome described here represents the only CPV genome described in the USA from the 2022 season, despite news of CPV outbreak-associated fatalities in dogs in the USA. This highlights the need for more studies that document CPV complete or near complete genomes, as well as experimental studies, to further our understanding of its evolutionary process.

Comparison of high-frequency in-pipe SARS-CoV-2 wastewater-based surveillance to concurrent COVID-19 random clinical testing on a public U.S. university campus.

Wastewater-based epidemiology (WBE) is utilized globally as a tool for quantifying the amount of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) within communities, yet the efficacy of community-level wastewater monitoring has yet to be directly compared to random Coronavirus Disease of 2019 (COVID-19) clinical testing; the best-supported method of virus surveillance within a single population. This study evaluated the relationship between SARS-CoV-2 RNA in raw wastewater and random COVID-19 clinical testing on a large university campus in the Southwestern United States during the Fall 2020 semester. Daily composites of wastewater (24-hour samples) were collected three times per week at two campus locations from 16 August 2020 to 1 January 2021 (n = 95) and analyzed by reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) targeting the SARS-CoV-2 E gene. Campus populations were estimated using campus resident information and anonymized, unique user Wi-Fi connections. Resultant trends of SARS-CoV-2 RNA levels in wastewater were consistent with local and nationwide pandemic trends showing peaks in infections at the start of the Fall semester in mid-August 2020 and mid-to-late December 2020. A strong positive correlation (r = 0.71 (p < 0.01); n = 15) was identified between random COVID-19 clinical testing and WBE surveillance methods, suggesting that wastewater surveillance has a predictive power similar to that of random clinical testing. Additionally, a comparative cost analysis between wastewater and clinical methods conducted here show that WBE was more cost effective, providing data at 1.7% of the total cost of clinical testing ($6042 versus $338,000, respectively). We conclude that wastewater monitoring of SARS-CoV-2 performed in tandem with random clinical testing can strengthen campus health surveillance, and its economic advantages are maximized when performed routinely as a primary surveillance method, with random clinical testing reserved for an active outbreak situation.