Adding Bayesian disease mapping and co-factor analysis to the PAZ project in the Lake Victoria Crest, Kenya
The PAZ Project (People, Animals and their Zoonosis lead by E. Fevre, http://www.zoonotic-diseases.org/ home/Research/paz, funded by the Wellcome Trust) and its consecutive projects utilize innovative crossdisciplinary data analysis derived from Numerical Ecology to map, prioritize and deliver int...
| Autores principales: | , , , , |
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| Formato: | Conference Paper |
| Lenguaje: | Inglés |
| Publicado: |
International Symposia for Veterinary Epidemiology and Economics
2012
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/27766 |
| _version_ | 1855537484030541824 |
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| author | Dopfer, D. Amene, E. Doble, L. Glanville, William A. de Fèvre, Eric M. |
| author_browse | Amene, E. Doble, L. Dopfer, D. Fèvre, Eric M. Glanville, William A. de |
| author_facet | Dopfer, D. Amene, E. Doble, L. Glanville, William A. de Fèvre, Eric M. |
| author_sort | Dopfer, D. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | The PAZ Project (People, Animals and their Zoonosis lead by E. Fevre, http://www.zoonotic-diseases.org/
home/Research/paz, funded by the Wellcome Trust) and its consecutive projects utilize innovative crossdisciplinary
data analysis derived from Numerical Ecology to map, prioritize and deliver interventions
against infectious zoonotic diseases in people and their domestic animals. The interventions will be tailored
to the risk-driven needs of spatio-temporal clusters. The PAZ Project is undertaking a community based
cross sectional survey of humans and their livestock in a mixed crop-livestock farming system in the
Lake Victoria Crescent in East Africa. Comprehensive economic, social and disease – including HIV,
Malaria, Bovine Tuberculosis, blood and GI parasites – data are collected at the household and individual
animal and human level together with prevalence data of six neglected zoonoses. Diseases do not exist in
isolation. Ignoring interactions between multiple diseases, co-factors and reservoir species, results in the
misinterpretation of infection pressures and miscalculation of effects of interventions. Therefore, designing
intervention packages that are specifically targeted to clusters of disease and their co-factors, ensures that
the interventions are relevant, targeted and cost-effective. The data from the PAZ Project will be analyzed
using (1) Principal Component Analysis (PCA); (2) Cluster Analysis (CA); and finally (3) Bayesian Disease
Mapping (BDM) methods. The proposed oral presentation will describe the project and strategic plans for
and the preliminary outcomes of the data analysis. |
| format | Conference Paper |
| id | CGSpace27766 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2012 |
| publishDateRange | 2012 |
| publishDateSort | 2012 |
| publisher | International Symposia for Veterinary Epidemiology and Economics |
| publisherStr | International Symposia for Veterinary Epidemiology and Economics |
| record_format | dspace |
| spelling | CGSpace277662023-02-15T10:23:23Z Adding Bayesian disease mapping and co-factor analysis to the PAZ project in the Lake Victoria Crest, Kenya Dopfer, D. Amene, E. Doble, L. Glanville, William A. de Fèvre, Eric M. zoonoses animal diseases animal health The PAZ Project (People, Animals and their Zoonosis lead by E. Fevre, http://www.zoonotic-diseases.org/ home/Research/paz, funded by the Wellcome Trust) and its consecutive projects utilize innovative crossdisciplinary data analysis derived from Numerical Ecology to map, prioritize and deliver interventions against infectious zoonotic diseases in people and their domestic animals. The interventions will be tailored to the risk-driven needs of spatio-temporal clusters. The PAZ Project is undertaking a community based cross sectional survey of humans and their livestock in a mixed crop-livestock farming system in the Lake Victoria Crescent in East Africa. Comprehensive economic, social and disease – including HIV, Malaria, Bovine Tuberculosis, blood and GI parasites – data are collected at the household and individual animal and human level together with prevalence data of six neglected zoonoses. Diseases do not exist in isolation. Ignoring interactions between multiple diseases, co-factors and reservoir species, results in the misinterpretation of infection pressures and miscalculation of effects of interventions. Therefore, designing intervention packages that are specifically targeted to clusters of disease and their co-factors, ensures that the interventions are relevant, targeted and cost-effective. The data from the PAZ Project will be analyzed using (1) Principal Component Analysis (PCA); (2) Cluster Analysis (CA); and finally (3) Bayesian Disease Mapping (BDM) methods. The proposed oral presentation will describe the project and strategic plans for and the preliminary outcomes of the data analysis. 2012-08-20 2013-03-27T16:11:29Z 2013-03-27T16:11:29Z Conference Paper https://hdl.handle.net/10568/27766 en Limited Access International Symposia for Veterinary Epidemiology and Economics Dopfer, D., Amene, E., Doble, L., Glanville, W. de and Fèvre, E.M. 2012. Adding Bayesian disease mapping and co-factor analysis to the PAZ project in the Lake Victoria Crest, Kenya. Paper presented at the 13th conference of the International Society for Veterinary Epidemiology and Economics, Maastricht, the Netherlands, 20-24 August 2012. Durban, South Africa: International Symposia for Veterinary Epidemiology and Economics. |
| spellingShingle | zoonoses animal diseases animal health Dopfer, D. Amene, E. Doble, L. Glanville, William A. de Fèvre, Eric M. Adding Bayesian disease mapping and co-factor analysis to the PAZ project in the Lake Victoria Crest, Kenya |
| title | Adding Bayesian disease mapping and co-factor analysis to the PAZ project in the Lake Victoria Crest, Kenya |
| title_full | Adding Bayesian disease mapping and co-factor analysis to the PAZ project in the Lake Victoria Crest, Kenya |
| title_fullStr | Adding Bayesian disease mapping and co-factor analysis to the PAZ project in the Lake Victoria Crest, Kenya |
| title_full_unstemmed | Adding Bayesian disease mapping and co-factor analysis to the PAZ project in the Lake Victoria Crest, Kenya |
| title_short | Adding Bayesian disease mapping and co-factor analysis to the PAZ project in the Lake Victoria Crest, Kenya |
| title_sort | adding bayesian disease mapping and co factor analysis to the paz project in the lake victoria crest kenya |
| topic | zoonoses animal diseases animal health |
| url | https://hdl.handle.net/10568/27766 |
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