Yellow fever vaccine-associated viscerotropic disease: current perspectives
Bibliographic record
Abstract
PURPOSE: To assess those published cases of yellow fever (YF) vaccine-associated viscerotropic disease that meet the Brighton Collaboration criteria and to assess the safety of YF vaccine with respect to viscerotropic disease. LITERATURE SEARCH: Ten electronic databases were searched with no restriction of date or language and reference lists of retrieved articles. METHODS: All abstracts and titles were independently read by two reviewers and data independently entered by two reviewers. RESULTS: All serious adverse events that met the Brighton Classification criteria were associated with first YF vaccinations. Sixty-two published cases (35 died) met the Brighton Collaboration viscerotropic criteria, with 32 from the US, six from Brazil, five from Peru, three from Spain, two from the People's Republic of China, one each from Argentina, Australia, Belgium, Ecuador, France, Germany, Ireland, New Zealand, Portugal, and the UK, and four with no country stated. Two cases met both the viscerotropic and YF vaccine-associated neurologic disease criteria. Seventy cases proposed by authors as viscerotropic disease did not meet any Brighton Collaboration viscerotropic level of diagnostic certainty or any YF vaccine-associated viscerotropic disease causality criteria (37 died). CONCLUSION: Viscerotropic disease is rare in the published literature and in pharmacovigilance databases. All published cases were from developing countries. Because the symptoms are usually very severe and life threatening, it is unlikely that cases would not come to medical attention (but might not be published). Because viscerotropic disease has a highly predictable pathologic course, it is likely that viscerotropic disease post-YF vaccine occurs in low-income countries with the same incidence as in developing countries. YF vaccine is a very safe vaccine that likely confers lifelong immunity.
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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 | 0.013 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".