Evidence map›Paper›PMID 36167131›Full record

ArticleThe Science of the total environment2023

Does normalization of SARS-CoV-2 concentrations by Pepper Mild Mottle Virus improve correlations and lead time between wastewater surveillance and clinical data in Alberta (Canada): comparing twelve SARS-CoV-2 normalization approaches.

Rasha Maal-Bared, Yuanyuan Qiu, Qiaozhi Li, Tiejun Gao, Steve E Hrudey, Sudha Bhavanam, Norma J Ruecker, Erik Ellehoj, Bonita E Lee, Xiaoli Pang

Open access · greenAbstract read
In one paragraph

Article in The Science of the total environment, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 2 pooled it
9.7field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

49 citing papers in PubMed, 2 syntheses or guidelines pooled it, 104 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Rasha Maal-BaredQuality Assurance and Environment, EPCOR Water, Edmonton, Alberta, Canada. Electronic address: rmaalbar@epcor.com.
Yuanyuan QiuDepartment of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada.
Qiaozhi LiDepartment of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada.
Tiejun GaoDepartment of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada.
Steve E HrudeyDepartment of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada.
Sudha BhavanamDepartment of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada.
Norma J RueckerWater Quality Services, City of Calgary, Calgary, Alberta, Canada.
Erik EllehojEllehoj Redmond Consulting, Edmonton, Alberta, Canada.
Bonita E LeeDepartment of Paediatrics, University of Alberta, Edmonton, Alberta, Canada.
Xiaoli PangDepartment of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada; Public Health Laboratories (ProvLab), Alberta Precision Laboratories (APL), Edmonton, Alberta, Canada.
University of Alberta · CAAlberta Environment and Protected Areas · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wastewater-based surveillance (WBS) data normalization is an analyte measurement correction that addresses variations resulting from dilution of fecal discharge by non-sanitary sewage, stormwater or groundwater infiltration. No consensus exists on what WBS normalization parameters result in the strongest correlations and lead time between SARS-CoV-2 WBS data and COVID-19 cases. This study compared flow, population size and biomarker normalization impacts on the correlations and lead times for ten communities in twelve sewersheds in Alberta (Canada) between September 2020 and October 2021 (n = 1024) to determine if normalization by Pepper Mild Mottle Virus (PMMoV) provides any advantages compared to other normalization parameters (e.g., flow, reported and dynamic population sizes, BOD, TSS, NH3, TP). PMMoV concentrations (GC/mL) corresponded with plant influent flows and were highest in the urban centres. SARS-CoV-2 target genes E, N1 and N2 were all negatively associated with wastewater influent pH, while PMMoV was positively associated with temperature. Pooled data analysis showed that normalization increased ρ-values by almost 0.1 and was highest for ammonia, TKN and TP followed by PMMoV. Normalization by other parameters weakened associations. None of the differences were statistically significant. Site-specific correlations showed that normalization of SARS-CoV-2 data by PMMoV only improved correlations significantly in two of the twelve systems; neither were large sewersheds or combined sewer systems. In five systems, normalization by traditional wastewater strength parameters and dynamic population estimates improved correlations. Lead time ranged between 1 and 4 days in both pooled and site-specific comparisons. We recommend that WBS researchers and health departments: a) Investigate WWTP influent properties (e.g., pH) in the WBS planning phase and use at least two parallel approaches for normalization only if shown to provide value; b) Explore normalization by wastewater strength parameters and dynamic population size estimates further; and c) Evaluate purchasing an influent flow meter in small communities to support long-term WBS efforts and WWTP management.

Indexed as

COVID-19WastewaterAlbertaHumansLeadSARS-CoV-2TobamovirusWastewater-Based Epidemiological MonitoringLeadWastewaterCombined sewersCOVID-19Industrial wastewaterMobile populationsNormalizationWastewater-based epidemiology (WBE)

Identifiers

PMID36167131
PMCPMC9508694
OpenAlexW4296940672

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.