Literature DB >> 12419596

Modelling bovine trypanosomosis spatial distribution by GIS in an agro-pastoral zone of Burkina Faso.

Jean-François Michel1, Stéphane Dray, Stéphane de La Rocque, Marc Desquesnes, Philippe Solano, Gérard De Wispelaere, Dominique Cuisance.   

Abstract

Modelling of the spatial distribution of bovine trypanosomosis prevalence in Sideradougou district Burkina Faso was performed by using a combination of spatial and statistical analysis. Based on a comprehensive and geographically representative census of herds and farms in the area, more than 2000 cattle were randomly chosen and their blood sampled during field survey. Data on livestock farming practices were recorded for each farm. All data were mapped within a GIS to generate new information on spatial constraints in the area. Surveys results were analysed and serological prevalence data were modelled using logistic regression. The model allowed identification and quantification of risk factors. In a second step the statistical model was used predictively on the entire farm population in the area. This method was successful in predicting the serological prevalence for each individual herd in the sample, from their livestock management patterns and spatial location. Predicted prevalences were represented within the GIS, taking daily movements of animals into account. Spatial distribution of prevalence would illustrate specific locations at risk from an epidemiological viewpoint. It gives evidence that the hydrological network and land occupation patterns in the savanna-type countryside are playing an important part when structuring a so-called "trypanosomosis space".

Entities:  

Mesh:

Year:  2002        PMID: 12419596     DOI: 10.1016/s0167-5877(02)00120-4

Source DB:  PubMed          Journal:  Prev Vet Med        ISSN: 0167-5877            Impact factor:   2.670


  2 in total

1.  Spatial variation in springtime food resources influences the winter body mass of roe deer fawns.

Authors:  Nathalie Pettorelli; Stephane Dray; Jean-Michel Gaillard; Daniel Chessel; Patrick Duncan; Andrew Illius; Nadine Guillon; Francois Klein; Guy Van Laere
Journal:  Oecologia       Date:  2003-08-15       Impact factor: 3.225

2.  The use of geographic information system and 1860s cadastral data to model agricultural suitability before heavy mechanization. A case study from Malta.

Authors:  Gianmarco Alberti; Reuben Grima; Nicholas C Vella
Journal:  PLoS One       Date:  2018-02-07       Impact factor: 3.240

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.