Environmental and demographic risk factors for campylobacteriosis: do various geographical scales tell the same story?
Bibliographic record
Abstract
BACKGROUND: Campylobacter is a common cause of bacterial gastro-enteritis characterized by multiple environmental sources and transmission pathways. Ecological studies can be used to reveal important regional characteristics linked to campylobacteriosis risk, but their results can be influenced by the choice of geographical units of analysis. This study was undertaken to compare the associations between the incidence of campylobacteriosis in Quebec, Canada and various environmental characteristics using seven different sets of geographical units. METHODS: For each set of geographical unit, a conditional autoregressive model was used to model the incidence of reported cases of campylobacteriosis according to environmental (poultry density, ruminant density, slaughterhouse presence, temperature, and precipitation) and demographic (population density, level of education) characteristics. Models were compared in terms of number of significant predictors, differences in direction and magnitude of predictors, and fit of the models. RESULTS: In general, the number of significant predictors was reduced as the aggregation level increased. More aggregated scales tend to show larger but less precise estimates for all variables, with the exception of slaughterhouse presence. Regional characteristics associated with an increased regional risk of campylobacteriosis, for at least some geographical units, were high ruminant density, high poultry density, high population density, and presence of a large poultry slaughterhouse, whereas a reduction in risk was associated with a lower percentage of people with diplomas, a lower level of precipitation, and warmer temperature. Two clusters of elevated residual risk were observed, with different location and size depending on the geographical unit used. CONCLUSIONS: Overall, our results suggest that the use of municipality or census consolidated subdivision were the most optimal scales for studying environmental determinants of campylobacteriosis at a regional level. This study highlights the need for careful selection and analysis of geographical units when using ecological study designs.
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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 | 0.001 | 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".