A systematic review on the seroprevalence and global distribution pattern of paratuberculosis in small ruminant and deer herds
Bibliographic record
Abstract
Paratuberculosis, also known as Johne's disease, is a chronic wasting disease caused by Mycobacterium avium subs paratuberculosis (MAP) in ruminants. Paratuberculosis causes a significant reduction of milk production in the affected dairy sheep or goats and increase the cost of diagnosis, treatment, and culling of the infected animals. Paratuberculosis is currently recognised as a disease of major economic significance in cattle, sheep, goats, and wild ruminants globally. Recent reports also suggest that paratuberculosis affects wild ruminants and farmed deer. Despite the widespread occurrence of MAP, there are variations in the seroprevalence and global distribution patterns of disease among small ruminants and deer herds due to the influence of interacting epidemiological variables in different places. This systematic review aims to provide insights on the current global seroprevalence status and distribution pattern of paratuberculosis among small ruminants and deer herds. The review compiled, analyzed, and narratively synthesized 36 eligible research articles published between January 1, 2010, and January 31, 2024, from the SCOPUS and PubMed databases based on the 22-point Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist. The average global seroprevalence of paratuberculosis in sheep was 14.02% (0.7–66.8), with the highest rate in Canada (66.8%) and the lowest in Austria (0.7%). Comparatively, the average global seroprevalence in goats was 18.44% (0.3–83), with the highest rate in Canada (83%) and the lowest in the West Indies (0.3%). The average global prevalence of paratuberculosis in deer was 14.76% (3.7–30.2), with the highest rate in Spain (30.2%) and the lowest rate in the Czech Republic (3.7%). This review revealed that Canada is a hot spot for both caprine and ovine paratuberculosis, and there were higher global seroprevalence rates in goats than sheep and deer. The lack of data on the seroepidemiology of paratuberculosis among small ruminant stock in Southeast Asia and other regions is a gap in our current knowledge of its distribution. Therefore, seroprevalence surveys of paratuberculosis among small ruminant and deer livestock are required to furnish information for planning suitable interventions in these areas.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.016 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".