Comparison of vaccination strategies for the control of dog rabies in Machakos District, Kenya
Bibliographic record
Abstract
Demographic and epidemiological field data were used in a deterministic model to describe dog rabies transmission in Machakos District, Kenya and to predict the impact of potential vaccination strategies for its control. The basic reproduction number (R0) was estimated to be 2.44 (1.52-3.36, 95% confidence limits). There were three key model predictions. The first was that a threshold dog density (K(T)) of 4.5 dogs km(-2) (3.8-5.2 dogs km(-2), 95% confidence limits) was required to maintain transmission. The second was that the estimated annual vaccination rate of 24% failed to decrease incidence and actually increased the stability of transmission and may be counter-productive. Thirdly, to control rabies, it was predicted that 59% (34%-70%, 95% confidence limits) of dogs should be vaccinated at any one time. This requires approximately 70% coverage for annual but only 60% coverage for semi-annual vaccination campaigns. Community-level vaccination trials are needed to test these predictions.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".