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

Bowes, Devin A.; Driver, Erin M.; Kraberger, Simona; Fontenele, Rafaela S.; Holland, LaRinda A; Wright, Jillian; Johnston, Bridger; Savic, Sonja; Newell, Melanie Engstrom; Adhikari, Sangeet; Kumar, Rahul; Goetz, Hanah; Binsfeld, Allison; Nessi, Kaxandra; Watkins, Payton; Mahant, Akhil; Zevitz, Jacob; Deitrick, Stephanie; Brown, Philip N.; Dalton, Richard; Garcia, Chris; Inchausti, Rosa; Holmes, Wydale; Tian, Xiao‐Jun; Varsani, Arvind; Lim, Efrem S.; Scotch, Matthew; Halden, Rolf U.

doi:10.1016/s2666-5247(22)00289-0

Cited by 23 publications

(10 citation statements)

References 22 publications

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“…It must be noted that other passive surveillance techniques are being explored. These include wastewater surveillance [ 25 ] and the use of automated contract tracing utilizing smartphone applications [ 26 ]. While wastewater surveillance can provide a directional understanding of the amount of infection within a particular sewer shed, it does not generally provide information necessary for case cluster detection, only presence.…”

Section: Discussionmentioning

confidence: 99%

Automatic case cluster detection using hospital electronic health record data

DeWitt

Wierzba

2023

Biology Methods and Protocols

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Case detection through contact tracing is a key intervention during an infectious disease outbreak. However, contact tracing is an intensive process where a given contact tracer must locate not only confirmed cases, but identify and interview known contacts. Often these data are manually recorded. During emerging outbreaks, the numbers of contacts could expand rapidly and beyond this, when focused on individual transmission chains, larger patterns may not be identified. Understanding if particular cases can be clustered and linked to a common source can help to prioritize contact tracing effects and understand underlying risk factors for large spreading events. Electronic health records systems are used by the vast majority of private health care systems across the United States, providing a potential way to automatically detect outbreaks and connect cases through already collected data. In this analysis we propose an algorithm to identify case clusters within a community during an infectious disease outbreak using Bayesian probabilistic case linking and explore how this approach could supplement outbreak responses; especially when human contact tracing resources are limited.

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Section: Discussionmentioning

confidence: 99%

Automatic case cluster detection using hospital electronic health record data

DeWitt

Wierzba

2023

Biology Methods and Protocols

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“…Subsequently, 200 µL of each sample concentrate were extracted using a Qiagen RNeasy Mini Kit (Hilden, Germany) to a final volume of 50 µL. Additional method details can be found in previous work (Bowes et al, 2023; Wright et al, 2022).…”

Section: Methodsmentioning

confidence: 99%

Human adenovirus outbreak at a university campus monitored by wastewater and clinical surveillance

Holland,

Smith,

Holland

et al. 2024

Preprint

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Areas of dense population congregation are prone to experience respiratory virus outbreaks. We monitored wastewater and clinic patients for the presence of respiratory viruses on a large, public university campus. Campus sewer systems were monitored in 16 locations for the presence of viruses using next generation sequencing over 22 weeks in 2023. During this period, we detected a surge in human adenovirus (HAdV) levels in wastewater. Hence, we initiated clinical surveillance at an on-campus clinic from patients presenting with acute respiratory infection. From whole genome sequencing of 123 throat and/or nasal swabs collected, we identified an outbreak of HAdV, specifically of HAdV-E4 and HAdV-B7 genotypes overlapping in time. The temporal dynamics and proportions of HAdV genotypes found in wastewater were corroborated in clinical infections. We tracked specific single nucleotide polymorphisms (SNPs) found in clinical virus sequences and showed that they arose in wastewater signals concordant with the time of clinical presentation, linking community transmission of HAdV to the outbreak. This study demonstrates how wastewater-based epidemiology can be integrated with surveillance at ambulatory healthcare settings to monitor areas prone to respiratory virus outbreaks and provide public health guidance.

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“…SARS-CoV-2 case rates were downloaded from a publicly available data dashboard reporting case rate for Tempe zip codes from the Maricopa County Department of Public Health. SARS-CoV-2 wastewater viral load was measured via RT-qPCR as previously described (40) and resulting data was obtained from the Tempe COVID-19 Wastewater Collection Data Dashboard. Aggregated SARS-CoV-2 genome copies per liter was calculated as the median genome copies per liter of wastewater across all sites within collection week.…”

Section: Sars-cov-2 Analysismentioning

confidence: 99%

Seasonality of Respiratory, Enteric and Urinary Viruses Revealed by Wastewater Genomic Surveillance

Smith,

Maqsood,

Sullins

et al. 2024

Preprint

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Wastewater surveillance can reveal population-level infectious disease burden and emergent public health threats can be reliably assessed through wastewater surveillance. While molecular methods for wastewater monitoring of microorganisms have traditionally relied on PCR-based approaches, next-generation sequencing can provide deeper insights via genomic analyses of multiple diverse pathogens. We conducted a year-long sequencing surveillance of 1,408 composite wastewater samples collected from 12 neighborhood-level access points in the Greater Tempe area, Arizona, USA, and show that variation in wastewater viromes is driven by seasonal time and location. Wastewater virome temporal dynamics were influenced in a cyclical manner, with the most dissimilarity between samples 23 weeks apart (i.e., winter vs summer, spring vs fall). We identified diverse urinary and enteric viruses including polyomaviruses, astroviruses and noroviruses, and showed that their genotypes/subtypes shifted across season. We show that while wastewater data of certain respiratory viruses like SARS-CoV-2 strongly correlate with clinical case rates, laboratory-reported case incidences were discordant with surges of high viral load in wastewater for other viruses like human coronavirus 229E. These results demonstrate the utility of wastewater sequencing for informing decision making in public health.

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

Cited by 23 publications

References 22 publications

Automatic case cluster detection using hospital electronic health record data

Automatic case cluster detection using hospital electronic health record data

Human adenovirus outbreak at a university campus monitored by wastewater and clinical surveillance

Seasonality of Respiratory, Enteric and Urinary Viruses Revealed by Wastewater Genomic Surveillance

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