Sero-prevalence and risk factors for sheeppox in Kordofan states in Sudan
Bibliographic record
Abstract
Abstract Background Sheeppox and goatpox are viral diseases of sheep and goats causing high morbidity and mortality leading to large economic losses for producers. The viruses are transmitted primarily through direct contact between infected animals. Understanding the sero-prevalence, risk factors and producers knowledge of the disease is critical for implementation of control strategies. Methods A cross-sectional survey was performed in the Kordofan region, from March to September 2011 using a virus neutralization test (VNT) and ELISA. The serology data was used to identify potential risk factors associated with sheep pox outbreaks. In addition, a questionnaire explored producer’s knowledge about the disease in the Sudan. Results The estimated overall sero-prevalence of sheeppox in the Kordofan region was 73.4% determined by virus neutralization and was prevalent in both South and North Kordofan states at 85% and 64% respectively. However, the seroprevalence determined using ELISA of sheeppox in South and North Kordofan states was 33% and 15% respectively. The risk factors identified were the breed, age, sex, species, movement patterns, herd size and geographic region. The questionnaire revealed that both nomadic and permanent farmers were generally aware of sheeppox as a disease, but most did not have a complete understanding of the disease. Greater than half of producers experienced the disease in the past 2 years and did not have their sheep vaccinated. Conclusions This study illustrates the disease burden of sheeppox in Sudan and demonstrates that for sero- surveillance, VNT is a more sensitive method compared to ELISA for detecting previously infected animals. Further education of producers of the disease and important of vaccination is required to control the disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".