Chikungunya: An Emerging Public Health Concern
Bibliographic record
Abstract
Purpose of Review: The worldwide spread of chikungunya over the past two decades calls for greater knowledge and awareness of the virus, its route of transmission, methods of diagnosis, and the use of available treatment and prevention measures. Recent Findings: mosquito-borne febrile disease, has spread from Africa and Asia to Europe and the Americas and from the tropics and subtropics to temperate regions. International travel is a pivotal influence in the emergence of chikungunya as a global public health threat, as evidenced by a growing number of published reports on travel-related chikungunya infections. The striking features of chikungunya are arthralgia and arthritis, and the disease is often mistaken for dengue. Although mortality is low, morbidity can be profound and persistent. Current treatment for chikungunya is supportive; chikungunya vaccines and therapeutics are in development. Travelers planning to visit areas where the mosquito vectors are present should be advised on preventive measures. Summary: Chikungunya is an emerging disease in the Americas. Frequent travel, the presence of at least two competent mosquito species, and a largely naïve human population in the Western Hemisphere create a setting conducive to future outbreaks. Awareness of the disease and its manifestations is critical to effectively and safely manage and limit its impact. Vaccines in late-stage clinical trials offer a new pathway to prevention.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".