Co-Circulation of Two Independent Clades and Persistence of CHIKV-ECSA Genotype during Epidemic Waves in Rio de Janeiro, Southeast Brazil
Bibliographic record
Abstract
The Chikungunya virus infection in Brazil has raised several concerns due to the rapid dissemination of the virus and its association with several clinical complications. Nevertheless, there is limited information about the genomic epidemiology of CHIKV circulating in Brazil from surveillance studies. Thus, to better understand its dispersion dynamics in Rio de Janeiro (RJ), one of the most affected states during the 2016-2019 epidemic waves, we generated 23 near-complete genomes of CHIKV isolates from two main cities located in the metropolitan mesoregion, obtained directly from clinical samples. Our phylogenetic reconstructions suggest the 2019-CHIKV-ECSA epidemic in RJ state was characterized by the co-circulation of multiple clade (clade A and B), highlighting that two independent introduction events of CHIKV-ECSA into RJ state have occurred between 2016-2019, both mediated from the northeastern region. Interestingly, we identified that the two-clade displaying eighteen characteristic amino acids changes among structural and non-structural proteins. Our findings reinforce that genomic data can provide information about virus genetic diversity and transmission dynamics, which might assist in the arbovirus epidemics establishing of an effective surveillance framework.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".