Abstract
This study used techniques in Geographical Information Systems (GIS) to explore the spatial patterns of bovine tuberculosis (TB) in the whole island of Ireland over an 11-year period. This is the first time that data pertaining to TB from the Republic of Ireland and Northern Ireland have been collated and examined in an all-Ireland context. The analyses were based on 198, 156 point locations representing active farms with cattle in Northern Ireland and the Republic of Ireland between the years 1996 and 2006. The results consist of a series of maps giving a visual representation of cattle populations and associated detected bTB levels on the island of Ireland over this time interval.
Highlights
Bovine tuberculosis (TB; caused by Mycobacterium bovis infection) remains an important public and animal health issue throughout the island of Ireland, which includes the jurisdictions of Northern Ireland and the Republic of Ireland
In the Republic of Ireland, the Land Parcel Identification System (LPIS), a spatial database created by the Department of Agriculture, Fisheries and Food (DAFF) to manage European Union Area Aid claims, contains the location of the farm areas claimed by 95% of all farms
In 2006, TB risk was at a lower level, but remained widely dispersed, Figure 6: Thematic map of animal-level TB risk each year on the island of Ireland from 1996 to 2006
Summary
Bovine tuberculosis (TB; caused by Mycobacterium bovis infection) remains an important public and animal health issue throughout the island of Ireland, which includes the jurisdictions of Northern Ireland and the Republic of Ireland. Disease data are commonly recorded at a point level and assigned to an area and represented as a choropleth map (for eg., More 2006; Centers for Disease Control and Prevention 2007; More and Collins 2008). The aim of this project is to use GIS to explore the spatiotemporal patterns of bTB reactors in the whole island over an 11-year period using techniques that incorporate methodologies of both point-process and polygon based visualisation
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