Return of the founder Chikungunya virus to its place of introduction into Brazil is revealed by genomic characterization of exanthematic disease cases
Bibliographic record
Abstract
Between June 2017 and August 2018, several municipalities located in Bahia state (Brazil) reported a large increase in the number of patients presenting with febrile illness similar to that of arboviral infections. Using a combination of portable whole genome sequencing, molecular clock and epidemiological analyses, we revealed the return of the CHIKV-ECSA genotype into Bahia. Our results show local persistence of lineages in some municipalities and the re-introduction of new epidemiological strains from different Brazilian regions, highlighting a complex dynamic of transmission between epidemic seasons and sampled locations. Estimated climate-driven transmission potential of CHIKV remained at similar levels throughout the years, such that large reductions in the total number of confirmed cases suggests a slow, but gradual accumulation of herd-immunity over the 4 years of the epidemic in Bahia after its introduction in 2014. Bahia remains a reservoir of the genetic diversity of CHIKV in the Americas, and genomic surveillance strategies are essential to assist in monitoring and understanding arboviral transmission and persistence both locally and over large distances.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".