Epidemiology and genetic diversity of circulating dengue viruses in Medellin, Colombia: a fever surveillance study
Bibliographic record
Abstract
BACKGROUND: Dengue fever is a major public health problem in Colombia. A fever surveillance study was conducted for evaluation of the clinical, epidemiological, and molecular patterns of dengue, prior to Chikungunya and Zika epidemics. METHODS: In November 2011-February 2014, a passive facility-based surveillance was implemented in Santa Cruz Hospital, Medellin, and enrolled eligible febrile patients between 1 and 65 years-of-age. Acute and convalescent blood samples were collected 10-21 days apart and tested for dengue using IgM/IgG ELISA. RNA was extracted for serotyping using RT-PCR on acute samples and genotyping was performed by sequencing. RESULTS: Among 537 febrile patients enrolled during the study period, 29% (n = 155) were identified to be dengue-positive. Only 7% of dengue cases were hospitalized, but dengue-positive patients were 2.6 times more likely to be hospitalized, compared to non-dengue cases, based on a logistic regression. From those tested with RT-PCR (n = 173), 17 were dengue-confirmed based on PCR and/or virus isolation showing mostly DENV-3 (n = 9) and DENV-4 (n = 7) with 1 DENV-1. Genotyping results showed that: DENV-1 isolate belongs to the genotype V or American/African genotype; DENV-3 isolates belong to genotype III; and DENV-4 isolates belong to the II genotype and specifically to the IIb sub-genotype or linage. CONCLUSIONS: Our surveillance documented considerable dengue burden in Santa Cruz comuna during non-epidemic years, and genetic diversity of circulating DENV isolates, captured prior to Chikungunya epidemic in 2014 and Zika epidemic in 2015. Our study findings underscore the need for continued surveillance and monitoring of dengue and other arboviruses and serve as epidemiological and molecular evidence base for future studies to assess changes in DENV transmission in Medellin, given emerging and re-emerging arboviral diseases in the region.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".