Measles importations by international travelers, GeoSentinel 2019–2025
Bibliographic record
Abstract
BACKGROUND: The global resurgence of measles is a threat to measles elimination campaigns. Measles importations by international travelers have been identified as a risk factor for outbreaks. METHODS: We reviewed measles cases among international travelers and migrants reported to the GeoSentinel network. RESULTS: From May 2019 through June 2025, GeoSentinel recorded 53 measles cases among travelers imported into 15 different countries. Travelers of all age groups were affected, and 74 % were 21 years or older. Thirty-three travelers (61 %) were hospitalized. Seventy-nine percent of cases reported no or unknown history of vaccination against measles. CONCLUSIONS: Against a background of increasing numbers of measles cases and outbreaks globally, GeoSentinel observed a stable trend of measles importations by international travelers. Measles caused considerable morbidity among travelers. Immunization effectively prevents measles in more than 97 % of individuals. Pretravel consultations provide an important opportunity to promote vaccination coverage for all vaccine-preventable diseases, including measles.
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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 | 0.000 | 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) | 0.001 | 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".