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

Abstract

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.

Figure 1

Schematic of the Arizona State University and City of Tempe academic and municipal partnership A WBE monitoring network established in 2018 for monitoring opioid use was leveraged to enable a rapid transition to monitoring SARS-CoV-2 during the COVID-19 global pandemic (starting in 2020) with work products including the world's first WBE-informed public-facing interactive online dashboards to combat the opioid and COVID-19 epidemics through a data-driven targeted public health response. ASU=Arizona State University. LC-MS/MS=liquid chromatography-tandem mass spectrometry. RT-qPCR=reverse transcription quantitative PCR. WBE=wastewater-based epidemiology.

Figure 2

Comparison of wastewater-derived viral loads of SARS-CoV-2 (genome copies per day) and clinical cases of COVID-19 in Tempe, Arizona (A) SARS-CoV-2 genome copies per day in the four zip codes (ZC-1 to ZC-4) and in aggregate, overlaid with newly reported clinical cases. Numbers are the number of days the wastewater signal leads (positive number) or lags (negative number) clinical cases, determined by root mean square error analysis. (B) Reported number of saliva-based tests processed per day for faculty, staff, and the general public (grey), students only (black), and a 7-day trailing average (green dotted line). Vertical grey dotted lines indicate noteworthy enhancements of testing efficacy: laboratory capacity increased to 12 000 tests per day in November, 2020, and January, 2021 was reported to have the highest volume of saliva-based tests received. These improvements are a probable cause of wastewater monitoring transitioning from a leading to lagging or real-time indicator of community viral presence.

Figure 3

Wastewater-derived SARS-CoV-2 viral load (genome copies per day) compared with county-level and state-level clinical datasets (A) Peaks in SARS-CoV-2 viral load (genome copies per day) in Tempe, Arizona wastewater compared with Maricopa County, Arizona new clinically detected cases of COVID-19, and COVID-19-related hospitalisations and deaths. Numbers are the number of days the wastewater signal leads (positive number) or lags (negative number) clinical cases. (B) Total number of diagnostic tests for COVID-19 conducted per week (light pink) in the state of Arizona, demonstrating increased testing efficacy starting from 30 available sites state-wide in May, 2020, to more than 500 available testing sites state-wide in October, 2020. (C) Reported timeline of events during time of study serves to support that as clinical testing improved throughout the pandemic, wastewater monitoring transitioned from a leading indicator to a lagging or real-time indicator. *The Arizona State University Biodesign Clinical Testing Laboratory developed a saliva-based test in partnership with the Arizona Department of Health Services to offer free, accessible testing state-wide. †Three universities: Arizona State University, Northern Arizona University, and University of Arizona.