1760. Wastewater-based surveillance for influenza A and RSV and its correlation with clinical disease in Edmonton, Alberta
Bibliographic record
Abstract
Abstract Background Wastewater (WW)-based surveillance (WBS) of SARS-CoV-2 has been shown to provide a leading indicator to COVID-19 clinical disease including confirmed cases and associated-hospitalizations. To this point, however, longitudinal monitoring of endemic respiratory diseases such as influenza A (IAV) and respiratory syncytial virus (RSV) have minimally been explored. We sought to correlate WW measured endemic virus RNA from municipal WW treatment plants (WWTP) with clinical data to understand WBS performance for endemic respiratory disease in Alberta’s capital city, Edmonton. Methods WW was collected thrice weekly from the two WWTP servicing the Edmonton-area (population ∼1.3 million) between Jan’22 & Feb’23. 24-hour composite samples were processed by Centricon ultracentrifugation, and RNA extracted. IAV, and RSV were quantified in duplicate by established RT-qPCR assays. WW SARS-CoV-2 level values adjusted by population served by each WWTP were compared with clinical cases in sewershed-matched areas in Edmonton Health Zone. Daily IAV and RSV case numbers were generated from IAV and RSV specimen testing data extracted from Alberta Precision Laboratory-Public Health Laboratory and FSA of the specimens was used to create the sewershed-matched case data. Results A total of 361 wastewater samples from the two WWTPs were collected between January 2022 and February 2023: 83 (30%) tested positive for IAV and 185 (51.2%) for RSV. Over two respiratory viral seasons, 2021/2022 and 2022/2023, IAV peaked in May/June 2022 and again in Nov/Dec 2022. IAV and RSV measured in WW positively correlated with daily confirmed clinical cases within the Edmonton Health Zone (Pearson correlation IAV, r2=0.61, p< 0.0001; RSV, r2=0.65, p< 0.0001). Relative to the 2021/2022 season, the WW RSV peak in the 2022/2023 season occurring in November/January was much greater. Figure 1 Population normalized Flu A concentrations in wastewater vs. population normalized case rates in the Edmonton Health Zone. Figure 2 Population normalized RSV concentrations in wastewater vs. population normalized case rates in the Edmonton Health Zone. Conclusion WBS of IAV and RSV demonstrated strong correlations with clinically confirmed diseases in sewershed-matched areas in Edmonton, Alberta. WBS enables objective, inclusive and unbiased monitoring of endemic respiratory viral disease activity. Disclosures All Authors: No reported disclosures
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".