Seroprevalence and risk factors of Neospora caninum and Bovine Viral Diarrhoea Virus in smallholder dairy cattle in Kenya
Bibliographic record
Abstract
Little is known of the risk factors associated with occurrence of Neospora caninum and Bovine Viral Diarrhoea Virus (BVDV) infection in Kenya. This cross-sectional study hypothesized that there are significant biosecurity measures associated with N. caninum and BVDV infections on smallholder dairy farms in Kenya that could be adopted to reduce seroprevalence and impacts. From 158 randomly selected farms in Meru County, Kenya, 470 serum samples were collected from dairy cattle (over six months of age and unvaccinated for these two pathogens). Sera were analyzed for antibodies to N. caninum and antibodies and antigens to BVDV. Data on risk factors were obtained through face-to-face interviews with the farmers. Multivariable logistic regression models were used to identify significant risk factors associated with seropositivity for the pathogens. The apparent seroprevalence of N. caninum, BVDV antibody, BVDV antigen, and co-infection with N. caninum and BVDV antibody and/or antigen were 35.1%, 47.1%, 36.2% and 18.5%, respectively. Risk factors associated with N. caninum antibody included: introducing milking cows into the farm, lending of cattle between farms, farm dogs having access to bovine aborted fetuses, and dogs whelping in the farm compound, with an interaction between the last two variables. BVDV antigen was associated with cattle having contact with pigs, and an interaction between cattle age and whether farms introduced new calves onto farms, and cattle age and whether visiting dairy farmers have access to the cow shed. Cows had higher odds of having BVDV antibodies compared to heifers. Factors associated with co-infection included cow parity, direct contact between dairy cattle, dogs and goats, and introducing new milking cows into the farms. Antibody and antigen results may be partly a function of classical swine fever virus or border disease virus interactions. Farmer education on these biosecurity measures is recommended, along with introduction of BVDV vaccination.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| 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".