Area-Level Clustering of Shiga Toxin–Producing <i>Escherichia coli</i> Infections and Their Socioeconomic and Demographic Factors in Ontario, Canada: An Ecological Study
Bibliographic record
Abstract
(STEC) infections are an important health burden for human populations in Ontario and worldwide. We assessed 452 STEC cases that were reported to Ontario's reportable disease surveillance system between 2015 and 2017. A retrospective scan statistic using a Poisson model was used to detect high-rate STEC clusters at the forward sortation area (FSA; the first three digits of a postal code) level. A significant spatial cluster in the southwest region of Ontario was identified. A case-case logistic regression analysis was applied to compare FSA-level socioeconomic and demographic characteristics among STEC cases included inside the spatial cluster with cases outside of the cluster. Cases included in the spatial cluster had higher odds of living in FSAs with a low median family income, low proportion of lone-parent families, and low proportion of the visible minority population. In addition, STEC cases inside the cluster had higher odds of coming from rural FSAs. Our study demonstrated that STEC cases were spatially clustered in Ontario and their clustering was associated with FSA-level socioeconomic and demographic determinants of cases.
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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) | 0.000 | 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".