Exploration of wastewater surveillance for Monkeypox virus
Bibliographic record
Abstract
Abstract The sudden emergence and spread of Monkeypox in non-endemic parts of the world is currently not well understood. Infections are often mis-diagnosed and surveillance strategies are scarce. Wastewater-based surveillance (WBS) of human Monkeypox virus (MPXV) can help supplement our current clinical surveillance and mitigation efforts. WBS has shown to be an effective tool in monitoring the spread of other infectious pathogens, such as SARS-CoV-2 and its variants, and has helped guide public health actions. In this study, we describe how WBS can be used to detect MPXV in wastewater. We conducted WBS for MPXV in 22 wastewater treatment plants (WWTPs) over a period of 14 weeks. Nucleic acids were extracted using the MagAttract PowerMicrobiome DNA/RNA extraction kit. Three real-time qPCR assays were assessed for the detection of MPXV in wastewater. These included the G2R assays (G2R_WA and G2R_G) developed by the Centers for Disease Control and Prevention (CDC) in 2010, as well as an in-house-developed assay (G2R_NML). The G2R_G (generic) assay was designed to detect both the Congo and West African clades (re-named to Clades one and two, respectively) of viruses while the G2R_WA assay was designed to detect the West African clade (Clade one). The G2R_NML assay was designed using reference genomes of the 2022 MPXV outbreak. Our results show that all three assays have similar limits of detection and are all able to detect the presence of MPXV in wastewater. Following detection through real time qPCR, Sanger sequencing was performed on the resulting amplicon products, with the assembled contigs then undergoing analysis using nucleotide Basic Local Alignment Search Tool (BLAST). Due in part to the longer amplicon size of the G2R_NML assay, a significantly greater number of positive detections were identified as originating from MPXV compared to the CDC G2R assays. The ability to detect trace amounts of MPXV in wastewater as well as obtain Sanger sequence confirmation, has allowed for the successful surveillance of this virus in wastewater.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".