The lower Saint Lawrence River region of Quebec, a hot spot for sheepfold-associated Q fever in Canada: Review of 258 cases
Bibliographic record
Abstract
Background: The lower Saint Lawrence river region (LSLRR), in Quebec, has a 10-fold higher incidence of Q fever compared to the provincial rate. This study aimed to review clinical cases and the Q fever risk exposure in this region. Methods: Data were retrieved from microbiology laboratory, medical records from Rimouski Regional Hospital and Public Health reports between 1991 and 2018. They were analyzed with Epi Info 7.2.2.6. Patients with confirmed acute, probable acute, and chronic Q fever were classified using standard case definitions and mapped according to the postal code, to assess the correlation between cases and sheep distribution. Results: Out of 295 cases, 258 were included (241 confirmed acute, seven probable acute, 10 chronic). Median age was 49 years, 76% were male. For acute cases, the prominent symptoms were fever (99%), headache (83%), chills (80%), sweating (72%), myalgia (69%), and fatigue (67%). Clinical presentation was mostly febrile syndrome with mild hepatitis (84%). A seasonal peak was observed from May to July (56% of acute cases). Most cases (56%) occurred within the two counties where sheep production was highest. Exposure to sheep was prominent 93%, including 64% direct contact (15% shepherds, 49% sheepfold visitors), 14% indirect contact, and 15% sheepfold neighbors. Conclusions: To our knowledge, this is one of the largest retrospective studies of Q fever cases reported in Canada. Q fever in Quebec LSLRR is associated mainly with sheep exposure. Fever and hepatitis were the most common manifestations. Preventive measures should be considered in this region to protect sheepfold workers, visitors, and their neighbors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".