An Estimate of the Incidence of Hepatitis A in Unimmunized Canadian Travelers to Developing Countries
Bibliographic record
Abstract
BACKGROUND: There is a paucity of data describing the risk of acquiring hepatitis A while traveling in the developing world. This paper uses available data to calculate the risk to Canadian travelers. METHODS: Information was gathered from Canadian and international sources on the following: the yearly incidence of hepatitis A among Canadians; the proportion of cases of hepatitis A associated with travel to developing countries; the number of days of such travel by Canadians per year; and the percentage of travelers immunized before departure. Calculations were performed on these figures to arrive at an estimated risk of infection for unimmunized Canadian travelers. RESULTS: The annual incidence of hepatitis A in Canada over the period 1996-2001, adjusted for underreporting, averaged 6.15 cases/100,000 people. During that time, Canadians traveled approximately 36.5 million days/year in developing countries. The literature shows that 4% to 28% (mean 16%) of cases are estimated to have been acquired abroad. It also shows that 14% to 24% (mean 19%) of such travelers are immunized before departure. Based on these figures, the risk of acquiring hepatitis A during 1 month of travel in the developing world is calculated to be approximately 1 case per 3,000 unimmunized travelers. CONCLUSION: Hepatitis A is an important travel-related disease, preventable by immunization. However, our calculations indicate that the risk of acquiring hepatitis A while traveling in the developing world is lower than some previously published estimates. The results represent an average for all types of travel to all such countries. The actual risk will vary considerably, depending on the destination and style of travel.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".