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Abstract / Description of output
administrative scales, and spatial tests were used to detect disease hotspots. A generalized mixed effects regression model was built to explore the relationships among Brucella serostatus, animals, and farm management factors. Seroprevalence was 2.39% (49/2048 cattle, 95% CI 1.7–3.1) across the study area and the Njombe Region represented the highest percentage with 15.5% (95% CI 11.0–22.0). Moreover, hotspots were detected in the Njombe and Kilimanjaro Regions. Mixed-effects models showed that having goats (OR 3.02, 95% C 1.22–7.46) and abortion history (OR 4.91, 95% CI 1.43–16.9) were significant risk factors for brucellosis. Education of dairy farmers regarding the clinical signs,
transmission routes, and control measures for brucellosis is advised. A One Health approach is required to study the role of small ruminants in cattle brucellosis and the status of brucellosis in dairy farmers in the Njombe and Kilimanjaro Regions.
Keywords / Materials (for Non-textual outputs)
- dairy cattle
- risk factors
FingerprintDive into the research topics of 'The Status and Risk Factors of Brucellosis in Smallholder Dairy Cattle in Selected Regions of Tanzania'. Together they form a unique fingerprint.
- 1 Finished
CTLGH: A global shared data biological sample resource to support productivity improvement for tropical livestock
1/10/15 → 31/03/22