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. 2002 Nov 29;56(1):19-32.
doi: 10.1016/s0167-5877(02)00121-6.

A global livestock production and health atlas (GLiPHA) for interactive presentation, integration and analysis of livestock data

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A global livestock production and health atlas (GLiPHA) for interactive presentation, integration and analysis of livestock data

A C A Clements et al. Prev Vet Med. .

Abstract

An interactive electronic atlas has been developed with the purpose of providing a scaleable overview of spatial and temporal variation in animal production and health-related information for decision and policy makers in national and international institutions. The information contained in the atlas is currently managed and presented using the Key Indicators Mapping System (KIMS), and will also be integrated using the Key Indicators Database System (KIDS). Both systems were developed by the World Agricultural Information Centre of the FAO (FAO-WAICENT), the former as a stand-alone application and the latter for access via the Internet. Components of the atlas include vector maps, livestock disease and production databases, rules for country-level disease risk classification and 'disease cards' containing basic background information on diseases included in the atlas. The disease data is currently based primarily on Office International des Epizooties (OIE) disease reports, and the livestock production data on the FAO-WAICENT database. The atlas is highly interactive and allows visual presentation of information using maps, tables and charts. It also contains links to relevant resource information on the Internet. Diseases covered in the animal health layer include most OIE List A diseases and a subset of OIE List B diseases. Extensive analyses have been conducted to develop a set of qualitative and semi-quantitative criteria that allow improved disease status classifications based on 5-years cumulative OIE disease reports, and official disease control declarations. Classification rules were determined depending on the epidemiological features of each disease and considering spatial heterogeneity of disease presence in local regions.

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