ArticleTropical animal health and production2023
Spatio-temporal epidemiology of livestock diseases in the variable semi-arid rangelands of northern Kenya.
Article in Tropical animal health and production, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 4 citations in OpenAlex.
- Molecular and serological evidence of Nairobi sheep disease virus in Haemaphysalis longicornis and sheep in eastern Shandong Peninsula, China.Journal of veterinary internal medicine · 2026Article
- Pastoralists' utilization and preferences for stakeholders and methods in livestock disease reporting and response in Northern Kenya: a participatory study.BMC veterinary research · 2026Article
- Geospatial and modelling analyses reveal diverse tick and tick-associated microbes in the East African Community.Infectious diseases of poverty · 2025Review
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Authors and funding
4 authors at 1 institution in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
Diseases affecting livestock can have significant impacts on the animal, humans and the economy. Participatory epidemiology and spatial analysis were conducted to assess livestock disease problems in Samburu County, northern Kenya. Key informants were selected purposively with the help of local leaders. Among the livestock, goats were identified to have the most economic importance. On the other hand Pestes des Petits Ruminants (PPR), Foot and Mouth Disease (FMD) and Camel Trypanosomiasis diseases were identified to have the highest impact on pastoral livelihood. Spatial analysis indicated that all the disease hotspots were closely related to the distribution of herds during different seasons of the year. Correlations between the mean annual rainfall and selected livestock diseases were significant for East Coast Fever (ECF) (r = - 0.767, p = 0.001, N = 15), Cattle Helminthiasis (r = 0.639, p = 0.010, N = 15), Cattle Anaplasmosis (r = 0.631, p = 0.012, N = 15) and Camel Pox (r = - 0.646, p = 0.044, N = 10). There was a strong relationship between seasonality and livestock disease epidemiology. Disease control efforts should be focused towards the hotspots in the wet season and dry season grazing areas.
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