Camel Mastitis: Prevalence, Risk Factors, and Isolation of Major Bacterial Pathogens in Gomole District of Borena Zone, Southern Ethiopia
Bibliographic record
Abstract
As of other dairy animals, dromedary camel could be affected by mastitis, a complex disease occurring worldwide among dairy animals, with heavy economic losses largely due to clinical and subclinical mastitis. Yet, little is known about the occurrence and potential risk factors exposing to lactating camel mastitis in Ethiopia. Consequently, a cross-sectional study was carried out from November 2018 to April 2019 so as to determine the prevalence, associated risk factors, and major bacterial pathogens causing mastitis in traditionally managed lactating camels in Gomole district of Borena Zone. Consequently, 348 lactating camels were examined for clinical and subclinical mastitis, using California Mastitis Test (CMT). The overall prevalence of mastitis was 22.4% (78/348), including clinical 4.3% (15/348) and subclinical 18.1% (63/348) cases, respectively, whereas the quarter level prevalence of mastitis was 16.6% (232/1,392). Of the total 1,392 examined teats, the right hind (RHQ) (4.3%, 60/1392) and left hind quarters (LHQ) (4.3%, 60/1392) were the most frequently infected quarter, whereas the left front quarter (LFQ) (3.9%, 55/1392) was the least infected quarter. Age, body condition score, and lactation stages were significantly associated ( <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mi>p</a:mi> <a:mo><</a:mo> <a:mn>0.05</a:mn> </a:math> ) with lactating camel mastitis prevalence among the putative risk factors. Among 312 quarters milk samples subjected to bacteriological examination, 69.9% (218/312) yielded mastitis causing pathogens, both Gram-positive and -negative bacterial isolates, while no growth was observed in 30.1% (94/312) of quarters sampled. Of the bacterial isolates obtained by culturing, Streptococcus spp. excluding Streptococcus agalactiae (S. agalactiae) (26.1%; 57/218) and Coagulase negative Staphylococci (22.9%, 50/218) were the dominant isolates identified, whereas S. agalactiae (3.2%, 7/218) was the least isolates obtained. The prevalence of camel mastitis in the study area was found to be considerably high. Hence, implementation of integrated approaches has great importance in the study setting for the prevention and control of mastitis so as to improve quality of camel milk, minimize economic loss, and prevent significant public health risks.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".