Perceived usefulness of syndromic surveillance in Ontario during the H1N1 pandemic
Bibliographic record
Abstract
BACKGROUND: Despite the growing popularity of syndromic surveillance, little is known about if or how these systems are accepted, utilized and valued by end users. This study seeks to describe the use of syndromic surveillance systems in Ontario and users' perceptions of the value of these systems within the context of other surveillance systems. METHODS: Ontario's 36 public health units, the provincial ministry of health and federal public health agency completed a web survey to identify traditional and syndromic surveillance systems used routinely and during the pandemic and to describe system attributes and utility in monitoring pandemic activity and informing decision-making. RESULTS: Syndromic surveillance systems are used by 20/38 (53%) organizations. For routine surveillance, laboratory, integrated Public Health Information System and school absenteeism data are the most frequently used sources. Laboratory data received the highest ratings for reliability, timeliness and accuracy ('very acceptable' by 92, 51 and 89%). Hospital/clinic screening data were rated as the most reliable and timely syndromic data source (50 and 43%) and ED visit data the most accurate (48%). During the pandemic, laboratory data were considered the most useful for monitoring the epidemiology and informing decision-making while ED screening and visit data were considered the most useful syndromic sources. CONCLUSIONS: End user perceptions are valuable for identifying opportunities for improvement and guiding further investments in public health surveillance.
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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 | 0.004 | 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 | 0.001 |
| 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".