Dog ecology and its implications for rabies control in Gwagwalada, Federal Capital Territory, Abuja, Nigeria
Bibliographic record
Abstract
The objectives of this study were to determine the characteristics of a dog population, including their accessibility to vaccination and health care, in urban and semiurban areas of Gwagwalada, Abuja, Nigeria. Direct street counts and a house-to-house survey of city streets were performed. A total of 451 households were surveyed comprising 43.7% urban and 53.3% semiurban areas. A total of 848 owned dogs were identified, along with 3,115 corresponding humans. With a dog-to-human ratio of 1:3.7, the dog population in the study area was estimated as 103,758. A total of 396 dogs were counted on the streets with the greater proportion (74%) in semiurban areas. Most dogs in semiurban areas (77.3%) had no certificate confirming vaccination against rabies, compared to 47.2% in urban areas (p = .004). The majority of dogs in the urban (60.9%) and semiurban (82.0%) were free roaming. In the multivariable model, age, presence of a collar, region, sex, use and having ever visited a veterinarian were significantly associated with rabies vaccination. The majority (125/197, 63.5%) of respondents with higher education were willing to pay more for the healthcare needs of their dogs as opposed to those with a lower level of education (93/251, 37.1%, p = .001). The study revealed a high dog population density, vaccination coverage below WHO recommendation of 70% and generally reduced healthcare-seeking behaviour among dog owners in Gwagwalada, Abuja, Nigeria.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.000 | 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".