Implication of sexual transmission of Zika on dengue and Zika outbreaks
Bibliographic record
Abstract
Dengue and Zika viruses belong to the same Flavivirus family and usually cocirculate within the same area. Both the viruses can be transmitted by a common mosquito species Aedes aegypti. However, non-vector-borne transmission of Zika virus, such as sexual transmission and vertical transmission, has been reported in recent studies. In this study, we develop a dengue-Zika coinfection model with a particular focus on the impact of Zika sexual transmission to the transmission dynamics of both dengue and Zika. Our sensitivity analysis shows that Zika sexual transmission has a significant influence on the Zika basic reproduction number. Consequently, Zika sexual transmission can lead Zika to be endemic within an area where vector-borne transmission only cannot. Theoretically, we prove that the disease-free equilibrium for dengue only model is always globally stable if the dengue basic reproduction number is less than 1. However, our cascade analysis and numerical simulations show that increasing the sexual transmission coefficient of Zika can also result in the persistence of dengue even though the dengue basic reproduction number is less than 1, due to the cocirculation of dengue and Zika and the antibody-dependent enhancement of Zika infection for dengue infection. Our numerical analyses also show that the endemic levels of Zika increase as the Zika sexual transmission probability increases.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".