Pepper mild mottle virus as a potential indicator of occupational exposure to airborne viruses in wastewater treatment plants
Bibliographic record
Abstract
Wastewater is a known carrier for human pathogenic viruses, with seasonal variations in concentrations, and wastewater treatment plant (WWTP) workers are a potentially overlooked occupational group regarding exposure to secondary aerosolized viruses. Exposure assessment of airborne pathogens is complicated by a lack of universal markers of viruses, no standardized sampling protocol, and challenges in detecting extremely low-abundant targets. In this study, we evaluate the risk of workers' exposure to 4 pathogens, Adenovirus, Norovirus GI and GII, and Influenza A and the Pepper mild mottle virus (PMMoV) as an indicator for aerosolized viruses from wastewater, in 3 WWTPs in the Oslo region, Norway. We collected personal and stationary air samples in summer and winter and used digital droplet PCR (ddPCR) to enable the detection of low-abundant targets. Pathogenic viruses were detected in 22% of all samples, with similar detection rates in personal and stationary samples, with a maximum concentration of 762 genome copies/m3 air. PMMoV was detected in 69% of all samples, with concentrations ranging from 28 to 9703 genome copies/m3 air. The pathogens and PMMoV were most frequently detected at the grids, biological cleansing, sedimentation basins, and sludge treatment/de-watering stations, and were associated with tasks such as flushing, cleaning, and maintenance of the same workstations. Overall, the concentration of pathogens and PMMoV in the air was low, but there is a potential for high point exposure which may pose a risk to workers' health and is increased by the nature of the workers' tasks. PMMoV may be a promising tool for assessing the overall potential for viruses with human waste origin aerosolized from sewage. To strengthen this indicator-based approach to occupational exposure assessment, we recommend validating PMMoV along with other potential indicators. Validation should include evaluating the correlation between these indicators and pathogens in both wastewater and bioaerosols.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".