Incidence and prevalence of rabies virus infections in tested humans and animals in Asia: A systematic review and meta-analysis study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: Rabies is a fatal neurological zoonotic disease affecting warm-blooded animals, causing nearly 60,000 human deaths annually, primarily in developing Asian and African countries (95 % of cases). This review examines the prevalence and incidence of rabies in tested humans and animals across Asia. Methods: We searched for scientific articles published in peer-reviewed journals between 2010 and 2024 in electronic databases. Ninety-seven publications were selected for the assessment of the rabies prevalence and nine for the assessment of the rabies incidence. Results: Overall, the prevalence of rabies based on the random-effects meta-analysis was 23 % (95 % CI 22.7-23.4) in tested animals and 52 % (95 % CI 40.2-63.8) in tested humans. Among animals, foxes had the highest test prevalence of 78.3 % (95 % CI 70.4 %-86.2 %) followed by dogs (38.1 %, 95 % CI 31.2 %-45 %). The incidence in tested animals was 0.5 % (95 % CI 0.4 %-0.6 %) and 0 % (95 % CI 0 %-0 %) in tested humans. Among animals, dogs have the highest incidence at 0.7 % (95 % CI 0.5 %-0.8 %). Conclusion: Many Asian countries have eradicated rabies by implementing control measures such as animal registration, quarantine, isolation, and mandatory mass vaccination. However, rising fox populations now pose a potential risk for rabies spread in the region.
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.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it