Between farm contacts in western Kenya: Implications for disease transmission
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Glanville, W.A. de, Bronsvoort, M.B. and Fèvre, E.M. 2012. Between farm contacts in western Kenya: Implications for disease transmission. Poster presented at the 13th conference of the International Society for Veterinary Epidemiology and Economics, Maastricht, the Netherlands, 20-24 August 2012. Durban, South Africa: International Symposia for Veterinary Epidemiology and Economics.
Permanent link to cite or share this item: https://hdl.handle.net/10568/27752
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The transmission dynamics of infectious disease depends on the frequency and type of contacts between susceptible and infectious individuals or groups. Between-farm contact structures have been defined in several countries, and have been widely used to model disease spread. In this study, we describe the farm contact structure in an area of western Kenya where the frequency and range of between-farm contacts was previously unknown. We focus on the specific between-herd contacts that are thought to be risk factors for the transmission of Brucella spp.. Through door-step interviews, all cattle farmers within a single 30 km2 administrative area, chosen as being representative of the diversity of cattle production systems present within the wider Western province of Kenya, were asked to report the identity and frequency of contacts with neighbouring herds, including co-grazing, the use of shared water points, and shared bulls. Moreover, the on and off-farm movement of cattle from within and outside the area under study, as well as a range of farm husbandry and production practices, were characterised. The between-farm contact network was investigated using social network analysis. To test for non-random interactions based on production type, we used multivariate statistical approaches to classify farms into distinct ‘sub-groups’ based on animal and farm management practices. This was followed by a set of ‘mixing matrix’ approaches in which herd assortativity based on sub-group membership was assessed. The contact network defined by this study will be used to inform disease transmission models for brucellosis in western Kenya. In particular, understanding the mixing patterns of different animal production systems in this mixed farming area will contribute to models describing animal reservoir dynamics for human brucellosis.