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Record W4403176524 · doi:10.1016/j.ijheh.2024.114477

Sewer transport conditions and their role in the decay of endogenous SARS-CoV-2 and pepper mild mottle virus from source to collection

2024· article· en· W4403176524 on OpenAlexaff
Élisabeth Mercier, Patrick M. D’Aoust, Walaa Eid, Nada Hegazy, Pervez Kabir, Shen Wan, Lakshmi Pisharody, Elizabeth Renouf, Sean Stephenson, Tyson E. Graber, Alex MacKenzie, Robert Delatolla

Bibliographic record

VenueInternational Journal of Hygiene and Environmental Health · 2024
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)MottlePepperVirologyCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakEndogenyVirusBiologyPlant virusMedicineFood scienceBiochemistry

Abstract

fetched live from OpenAlex

This study presents a comprehensive analysis of the decay patterns of endogenous SARS-CoV-2 and Pepper mild mottle virus (PMMoV) within wastewaters spiked with stool from infected patients expressing COVID-19 symptoms, and hence explores the decay of endogenous SARS-CoV-2 and PMMoV targets in wastewaters from source to collection of the sample. Stool samples from infected patients were used as endogenous viral material to more accurately mirror real-world decay processes compared to more traditionally used lab-propagated spike-ins. As such, this study includes data on early decay stages of endogenous viral targets in wastewaters that are typically overlooked when performing decay studies on wastewaters harvested from wastewater treatment plants that contain already-degraded endogenous material. The two distinct sewer transport conditions of dynamic suspended sewer transport and bed and near-bed sewer transport were simulated in this study at temperatures of 4 °C, 12 °C and 20 °C to elucidate decay under these two dominant transport conditions within wastewater infrastructure. The dynamic suspended sewer transport was simulated over 35 h, representing typical flow conditions, whereas bed and near-bed transport extended to 60 days to reflect the prolonged settling of solids in sewer systems during reduced flow periods. In dynamic suspended sewer transport, no decay was observed for SARS-CoV-2, PMMoV, or total RNA over the 35-h period, and temperature ranging from 4 °C to 20 °C had no noticeable effect. Conversely, experiments simulating bed and near-bed transport conditions revealed significant decreases in SARS-CoV-2 and total RNA concentrations by day 2, and PMMoV concentrations by day 3. Only PMMoV exhibited a clear trend of increasing decay constant with higher temperatures, suggesting that while temperature influences decay dynamics, its impact may be less significant than previously assumed, particularly for endogenous RNA that is bound to dissolved organic matter in wastewater. First order decay models were inadequate for accurately fitting decay curves of SARS-CoV-2, PMMoV, and total RNA in bed and near-bed transport conditions. F-tests confirmed the superior fit of the two-phase decay model compared to first order decay models across temperatures of 4 °C-20 °C. Finally, and most importantly, total RNA normalization emerged as an appropriate approach for correcting the time decay of SARS-CoV-2 exposed to bed and near-bed transport conditions. These findings highlight the importance of considering decay from the point of entry in the sewers, sewer transport conditions, and normalization strategies when assessing and modelling the impact of viral decay rates in wastewater systems. This study also emphasizes the need for ongoing research into the diverse and multifaceted factors that influence these decay rates, which is crucial for accurate public health monitoring and response strategies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.227

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.296
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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