Filariasis in Travelers Presenting to the GeoSentinel Surveillance Network
Bibliographic record
Abstract
BACKGROUND: As international travel increases, there is rising exposure to many pathogens not traditionally encountered in the resource-rich countries of the world. Filarial infections, a great problem throughout the tropics and subtropics, are relatively rare among travelers even to filaria-endemic regions of the world. The GeoSentinel Surveillance Network, a global network of medicine/travel clinics, was established in 1995 to detect morbidity trends among travelers. PRINCIPAL FINDINGS: We examined data from the GeoSentinel database to determine demographic and travel characteristics associated with filaria acquisition and to understand the differences in clinical presentation between nonendemic visitors and those born in filaria-endemic regions of the world. Filarial infections comprised 0.62% (n = 271) of all medical conditions reported to the GeoSentinel Network from travelers; 37% of patients were diagnosed with Onchocerca volvulus, 25% were infected with Loa loa, and another 25% were diagnosed with Wuchereria bancrofti. Most infections were reported from immigrants and from those immigrants returning to their county of origin (those visiting friends and relatives); the majority of filarial infections were acquired in sub-Saharan Africa. Among the patients who were natives of filaria-nonendemic regions, 70.6% acquired their filarial infection with exposure greater than 1 month. Moreover, nonendemic visitors to filaria-endemic regions were more likely to present to GeoSentinel sites with clinically symptomatic conditions compared with those who had lifelong exposure. SIGNIFICANCE: Codifying the filarial infections presenting to the GeoSentinel Surveillance Network has provided insights into the clinical differences seen among filaria-infected expatriates and those from endemic regions and demonstrated that O. volvulus infection can be acquired with short-term travel.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".