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

被引:19
作者
Clements, ACA
Pfeiffer, DU
Otte, MJ
Morteo, K
Chen, L
机构
[1] Univ London Royal Vet Coll, Div Epidemiol, Dept Vet Clin Sci, Hatfield AL9 7TA, Herts, England
[2] UN Food & Agr Org, Livestock Informat & Policy Branch, Rome, Italy
[3] UN Food & Agr Org, Informat Syst Serv, Rome, Italy
关键词
livestock disease; livestock production; visual analysis; Geographical Information Systems; disease atlas; database;
D O I
10.1016/S0167-5877(02)00121-6
中图分类号
S85 [动物医学(兽医学)];
学科分类号
0906 ;
摘要
An interactive electronic atlas has been developed with the purpose of providing a scaleable over-view 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. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:19 / 32
页数:14
相关论文
共 32 条
[1]  
[Anonymous], INTRO GUIDE DIS MAPP
[2]  
ATZENI P, 1999, DATABASE SYSTEMS CON, P465
[3]  
Bailey T. C., 1995, INTERACTIVE SPATIAL, P303
[4]   Towards an atlas of human helminth infection in sub-Saharan Africa: The use of geographical information systems (GIS) [J].
Brooker, S ;
Rowlands, M ;
Haller, L ;
Savioli, L ;
Bundy, DAP .
PARASITOLOGY TODAY, 2000, 16 (07) :303-307
[5]  
CAMERON AR, 1997, THESIS QUEENSLAND
[6]   EMPIRICAL BAYES ESTIMATES OF AGE-STANDARDIZED RELATIVE RISKS FOR USE IN DISEASE MAPPING [J].
CLAYTON, D ;
KALDOR, J .
BIOMETRICS, 1987, 43 (03) :671-681
[7]  
Conlon EM, 1999, DISEASE MAPPING AND RISK ASSESSMENT FOR PUBLIC HEALTH, P31
[8]   A climate-based distribution model of malaria transmission in sub-Saharan Africa [J].
Craig, MH ;
Snow, RW ;
le Sueur, D .
PARASITOLOGY TODAY, 1999, 15 (03) :105-111
[9]  
Ellis P. R., 1984, Development of animal production systems, P63
[10]   DISEASE MAPPING USING EMPIRICAL BAYES AND BAYES METHODS ON MORTALITY STATISTICS IN THE NETHERLANDS [J].
HEISTERKAMP, SH ;
DOORNBOS, G ;
GANKEMA, M .
STATISTICS IN MEDICINE, 1993, 12 (19-20) :1895-1913