Wastewater Surveillance for Communicable Diseases
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract

 This Horizon Scan summarizes the available information regarding wastewater epidemiology, or wastewater surveillance, for the detection of pathogens that cause communicable diseases.
 Wastewater surveillance can detect the presence of pathogens or chemical substances within the wastewater system and allows for the monitoring of a broad population with a single sample.
 Wastewater surveillance has been used for decades but has become more common since it was implemented around the world for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19. In Canada, wastewater surveillance is currently used for the detection of SARS-CoV-2, influenza, and respiratory syncytial virus.
 Studies conducted in Canada and internationally indicate that wastewater surveillance can be used as a reliable method for detecting pathogens at the population level.
 Future uses of wastewater surveillance may include monitoring of antibiotic use and antibiotic resistance, detection of cancers in the population, or assessing the prevalence of other infections within communities.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 it