Associating sporadic, foodborne illness caused by Shiga toxin-producing <i>Escherichia coli</i> with specific foods: a systematic review and meta-analysis of case-control studies
Bibliographic record
Abstract
Shiga toxin-producing Escherichia coli (STEC) infections are a significant public health issue, with foodborne transmission causing >1 million illnesses worldwide each year. We conducted a systematic review and meta-analysis (PROSPERO registry # CRD42017074239), to determine the relative association of different food types with sporadic illnesses caused by STEC. Searches were conducted from 01 August to 30 September 2017, using bibliographic and grey literature databases, websites and expert consultation. We identified 22 case-control studies of sporadic STEC infection in humans, from 10 countries within four World Health Organization subregions, from 1985 to 2012. We extracted data from 21 studies, for 237 individual measures in 11 food categories and across three status types (raw or undercooked, not raw and unknown). Beef was the most significant food item associated with STEC illness in the Americas and Europe, but in the Western Pacific region, chicken was most significant. These findings were not significantly moderated by the raw or cooked status of the food item, nor the publication year of the study. Data from the African, South-East Asian and Eastern Mediterranean subregions were lacking and it is unclear whether our results are relevant to these regions.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".