Risk Factors Associated with Bovine Tuberculosis and Molecular Characterization of<i>Mycobacterium bovis</i>Strains in Urban Settings in Niger
Bibliographic record
Abstract
A retrospective and a longitudinal survey were carried out at the abattoir of Niamey. Results showed a highly significant difference in suspected tuberculosis (TB) gross lesions among different animal species (P < 0.0001). The proportion of carcasses with TB-like lesions was 0.19% among cattle, 0.11% among camels, 0.001% among sheep and 0.0006% among goats. In cattle, cows are significantly more affected than the other categories (P < 0.001). Also in cattle, TB-like lesions are mostly localized in the lungs (92.77%) followed by the lymph nodes (50.87%) and the liver (32.40%). The prevalence of gross lesions compatible with bovine TB (BTB) is strongly influenced by the season (P < 0.0001), is closely correlated with the origin of the animals (P < 0.001) and has a negative impact on the weight of affected animals (P < 0.0001). Sixty-two samples of suspected TB gross lesions were subject to microbiological analysis and molecular typing of strains. Mycobacterium bovis was identified in 18 animals showing five different spoligotypes, belonging to type 'African 1' previously identified in Central and West Africa. In addition, a profile (SB1982) not previously reported distinguished by the absence of spacers 3, 4, 9, 16, 22, 30 and 39-43 has been characterized in this study. To assess risk factors for BTB transmission, a questionnaire on animal husbandry practices, food habits, and clinical signs of TB in animals and humans was submitted to the heads of 1131 randomly selected households. The main risk factors identified are consumption of unpasteurized milk (91%) and lack of hygiene within households (32-74%). Clinical signs that could be attributed to TB were also reported both in humans and in animals of the households.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".