Rabies vaccine is associated with decreased all-cause mortality in dogs
Bibliographic record
Abstract
Evidence suggests that rabies vaccine may have non-specific protective effects in animals and children. We analyzed four years of data (2012-2015) from an observational study of the health and demographics of a population of owned, free-roaming dogs in a low-income community in South Africa. The objective of this analysis was to assess the association between rabies vaccine and all-cause mortality in dogs, stratified by age group (0-3months, 4-11months, and 12months and older), and controlling for the effects of sex and number of dogs in the residence. Rabies vaccination reduced the risk of death from any cause by 56% (95% CI=16-77%) in dogs aged 0-3months, by 44% (95% CI=21-60%) in dogs aged 4-11months and by 16% (95% CI=0-29%) in dogs aged 12months and older. We hypothesize that the protective association between rabies vaccination status and all-cause mortality is due to a protective effect of rabies vaccine against diseases other than rabies. Existence of a strong non-specific protective effect of rabies vaccine on mortality in dogs would have implications for the design of dog rabies control programs that aim to eliminate dog-mediated human rabies cases. Further, we propose that owned domestic dogs in high mortality settings provide a useful animal model to better understand any non-specific protective effect of rabies vaccine in children, due to dogs' high numbers, high morbidity and mortality rates, relatively short lifespan, exposure to a variety of infectious and parasitic diseases, and shared environment with people.
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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 | 0.002 |
| 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) | 0.002 | 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".