Travel‐Related Shigellosis in Quebec, Canada: An Analysis of Risk Factors
Bibliographic record
Abstract
BACKGROUND: Travel-related shigellosis is not well documented in Canada although it is frequently acquired abroad and can cause severe disease. OBJECTIVES: To describe the epidemiology of travel-related cases of shigellosis for Quebec (Canada) and to identify high-risk groups of travelers. METHOD AND DATA SOURCES: We performed a random sampling of 335 shigellosis cases (from a total of 760 cases) reported in the provincial database of reportable diseases from January 1, 2004, to December 31, 2007. Each case was analyzed according to information available in the epidemiology questionnaire. Total number of trips by region from Statistics Canada was used as denominator to estimate the risk according to region of travel. RESULTS: Annually, between 43 and 54% of the shigellosis cases were reported in travelers, 45% of whom were aged between 20 and 44 years. Children under 11 years accounted for nearly 16% of cases, but represent only 4% of travelers. Most cases in travelers were serogroups Shigella sonnei (50%) or Shigella flexneri (45%). Almost 31% of cases were reported between January and March. The majority (64%) were acquired in Central America, Mexico, or the Caribbean. However, the Indian subcontinent, Africa, and South America had the highest ratio of number of cases per number of trips. Tourists represented 76% of the cases; 62% of them had traveled for <2 weeks. At least 15% of cases among travelers were hospitalized. CONCLUSIONS: In Quebec, travel-related cases of shigellosis represent a large burden of total cases. Short-term travelers are at risk, as well as young children. The majority of cases occur in the winter months, corresponding to the peak of travel to "sunshine destinations." Continuous efforts should be made to encourage all travelers to seek pre-travel care, and to inform primary care practitioners of health risks faced by their patients abroad, even for those going to resorts.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".