Patterns of Illness in Travelers Visiting Mexico and Central America: The GeoSentinel Experience
Bibliographic record
Abstract
BACKGROUND: Mexico and Central America are important travel destinations for North American and European travelers. There is limited information on regional differences in travel related morbidity. METHODS: We describe the morbidity among 4779 ill travelers returned from Mexico and Central America who were evaluated at GeoSentinel network clinics during December 1996 to February 2010. RESULTS: The most frequent presenting syndromes included acute and chronic diarrhea, dermatologic diseases, febrile systemic illness, and respiratory disease. A higher proportion of ill travelers from the United States had acute diarrhea, compared with their Canadian and European counterparts (odds ratio, 1.9; P < .0001). During the 2009 H1N1 influenza outbreak from March 2009 through February 2010, the proportionate morbidity (PM) associated with respiratory illnesses in ill travelers increased among those returned from Mexico, compared with prior years (196.0 cases per 1000 ill returned travelers vs 53.7 cases per 1000 ill returned travelers; P < .0001); the PM remained constant in the rest of Central America (57.3 cases per 1000 ill returned travelers). We identified 50 travelers returned from Mexico and Central America who developed influenza, including infection due to 2009 H1N1 strains and influenza-like illness. The overall risk of malaria was low; only 4 cases of malaria were acquired in Mexico (PM, 2.2 cases per 1000 ill returned travelers) in 13 years, compared with 18 from Honduras (PM, 79.6 cases per 1000 ill returned travelers) and 14 from Guatemala (PM, 34.4 cases per 1000 ill returned travelers) during the same period. Plasmodium vivax malaria was the most frequent malaria diagnosis. CONCLUSIONS: Travel medicine practitioners advising and treating travelers visiting these regions should dedicate special attention to vaccine-preventable illnesses and should consider the uncommon occurrence of acute hepatitis A, leptospirosis, neurocysticercosis, acute Chagas disease, onchocerciasis, mucocutaneous leishmaniasis, neurocysticercosis, HIV, malaria, and brucellosis.
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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 | 0.001 |
| 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) | 0.000 | 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".