Current perspectives on vaccines and therapeutics for Lassa Fever
Bibliographic record
Abstract
Lassa virus, the cause of deadly Lassa fever, is endemic in West Africa, where thousands of cases occur on an annual basis. Nigeria continues to report increasingly severe outbreaks of Lassa Fever each year and there are currently no approved vaccines or therapeutics for the prevention or treatment of Lassa Fever. Given the high burden of disease coupled with the potential for further escalation due to climate change the WHO has listed Lassa virus as a priority pathogen with the potential to cause widespread outbreaks. Several candidate vaccines have received support and have entered clinical trials with promising early results. This review focuses on the current state of vaccine and therapeutic development for LASV disease and the potential of these interventions to advance through clinical trials. The growing burden of LASV disease in Africa highlights the importance of advancing preclinical and clinical testing of vaccines and therapeutics to respond to the growing threat of LASV disease.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| 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".