Mastitis on selected farms in Wakiso district, Uganda: Burden, pathogens and predictors of infectivity of antimicrobial resistant bacteria in dairy herds
Bibliographic record
Abstract
BACKGROUND: Mastitis and associated antimicrobial resistance (AMR) are major challenges to the dairy industry worldwide. OBJECTIVE: This study aimed to expose the mastitis burden, causative bacteria and drivers for mastitis-causing multi-drug-resistant (MDR) Staphylococci infectivity in cows on dairy farms in Wakiso district, Uganda. METHODS: On 22 farms, practices were documented using questionnaires, and 175 cows were screened by the California mastitis test. Composite milk samples from the positive reactors were submitted to the laboratory for bacterial culture testing. Antimicrobial sensitivity testing by the Kirby Bauer disc diffusion method was done only on Staphylococci with a panel of 10 antimicrobials of clinical relevance. RESULTS: Mastitis was detected in 80.6% (n = 141) of the 175 sampled cows, of which sub-clinical mastitis (76.0%: n = 133) was predominant. The Chi-squared analysis hypothesized that cow age (p = 0.017), sub-county (p = 0.013), parity (p < 0.0001), sex of farm owner (p = 0.003), farm duration in dairy production (p = 0.048) and the use of milking salve (p = 0.006) were associated with mastitis. Coagulase-negative Staphylococci were the most prevalent (71.4%; n = 95), followed by Staphylococcus aureus (30.1%, n = 40). Staphylococci (76.3%; n = 135) were majorly resistant to penicillin and tetracycline. Only one isolate was phenotyped as a methicillin-resistant Staphylococcus specie (MRSS). The prevalences of MDR strains at cow and isolate level were 6.3% and 8.3%. The major MDR phenotype identified was penicillin-tetracycline-trimethoprim-sulphamethoxazole. The isolate detected as an MRSS exhibited the broadest MDR pattern. Cow parity was identified as a predictor of infectivity of mastitis-causing MDR Staphylococci in dairy herds. CONCLUSION: The high prevalence of mastitis and associated pathogen AMR found exposes possibilities of economic losses for the dairy sector warranting the need for farmer sensitization on the institution of proper mastitis prevention and control programs, with emphasis on milking hygiene practices and routine disease monitoring.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".