Abstract
A growing need exists for low cost systems to predict the status of diseases within geographical regions. The purpose of this research was to evaluate the usefulness of geographic information systems (GIS) and geostatistical (i.e.: Kriging) methods in predicting the prevalence and distribution of bovine tuberculosis (BTB) in the state of Jalisco, Mexico, based on a sample of herds. Two-thousand two-hundred and eighty-seven herds were electronically selected at random from the Jalisco´s State Commission for the Control and Eradication of Tuberculosis (COEETB) data base. Three different approaches (i.e.: a personal Global Positioning System [GPS], Mexico's National Institute for Statistics Geography and Informatics [INEGI]'s data base, and the Google Earth software) were used to identify the spatial location of each herd. Kriging, from ArcView Geostatistical Analyst was used to predict the prevalence of BTB. The efficacy of this prediction was determined by comparing two maps, one based on our 2,287 sample of herds and the map showing the distribution of Jalisco's total 48,766 herds. Similarity of BTB regional distribution in both maps shows that Kriging and geostatistics is an excellent tool to predict BTB distribution with major potential savings.
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