Dog Ecology and Population Studies in Lagos State, Nigeria
Bibliographic record
Abstract
Dog population dynamics have a major impact upon the effectiveness of rabies control strategies. As such, understanding domestic dog ecology has been recognized as central to the design of effective rabies control programmes. This study was conducted to determine the dog ecology in Lagos State using compound dog count and street dog count in the three senatorial districts (Lagos West, East and Central) of Lagos State from February, 2011 to January, 2012. A total of 546 questionnaires were distributed for the compound dog count and all were completed and returned. Various aspects of dog ecology were determined, including size, sex, breed of the dog population, management of dogs and rabies awareness among the respondents. Out of the 546 compounds surveyed, 518 (94.87%) owned at least one dog. A total of 1,427 dogs were counted from the street counts while a total of 1,447 dogs (2.8 dogs/compound) were counted from the compound count. The dogs comprised of 583 males and 864 females, out of which 64.10% are confined. The dog vaccination coverage in the dog population surveyed was 64.10% and administered majorly (91.30%) by veterinarians. Security (60%) and pets (26%) were the major reasons for keeping dogs. Majority (88.80%) of the respondents were aware of rabies and its mode of transmission, but still believed in the use of concoctions (40.40%), herbs (19.90%) and consumption of the organ of the offending dog (11.50%) for the treatment of rabies. The findings of this study showed a male: female ratio of dog to be 1:1.5 and a dog: human ratio of 1:5.6. There was also a responsible dog ownership as majority of the respondents do confine, vaccinate and provide food for their dogs. Vaccination coverage of the total dog population was however below the 70-80% target recommended by the World Health Organization to achieve herd immunity.
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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 | 0.004 | 0.001 |
| 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 | 0.001 |
| 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".