Rabies and Dog Bites Cases in Lagos State Nigeria: A Prevalence and Retrospective Studies (2006-2011)
Bibliographic record
Abstract
This study was carried out to determine the prevalence of rabies antigen in brain of dogs slaughtered for consumption and those that died in veterinary clinics as well as to obtain a 6-year retrospective data on dog bites/suspected dog rabies cases in Lagos State. Dog brain samples were collected from dog slaughter slabs and veterinary clinics (for dogs that died in clinics) across the Lagos state while data for retrospective studies (2006-2011) of dog bite/suspected rabies cases were collected from public (government owned) and private veterinary clinics across the state. Out of the 444 brain samples collected and tested for presence of rabies antigen using the direct fluorescent antibody technique (DFAT) only 7 (1.58%) were positive for the rabies antigen. A total of 196 dog bites/suspected rabies cases were encountered between January 2006 and December, 2011 in the veterinary clinics with adults been the major (55.61%) victims. Majority (96.43%) of the offending dogs were not quarantined at the time of bite and only one out of the quarantined dogs died and was confirmed positive for rabies antigen. The result of this study indicates that rabies antigen is present among dogs slaughtered in Lagos State and may pose a threat to public health. Though, available records showed that provocation of dogs was the major cause of dog bites and both children and adults fell victim of dog bites, there was a poor record keeping practice in the veterinary clinics across the state.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".