Controlling Dengue: Effectiveness of Biological Control and Vaccine in Reducing the Prevalence of Dengue Infection in Endemic Areas
Bibliographic record
Abstract
With the increased prevalence of dengue infection in tropical countries, concerned members of the public are now pressing their local health ministries to act immediately and effectively in managing the rising numbers of reported cases. This includes reviews of the methodologies and the effectiveness of current combative systems to find other possible novel approaches that might yield better results. One of those novel approaches is the integration of a parasite into mosquito vector, manipulating the parasite-host interaction to reduce the transmission of dengue in endemic hotspots. Another alternative is by Sanofi-Pasteur’s dengue vaccine that showed over 60.8% success rate in reducing severe dengue infection in children aged 9 - 16 during its final clinical implementation phase. This report will compare and contrast these two novel ideas to determine which of the approaches are more likely to be effective in the long run. The aspects covered will include the application, effectiveness, functionality, and problems with these approaches. The results could then be utilised by governments or organizations to select precise and effective methods in reducing the prevalence of dengue infections in their countries.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".