| Summary: | 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.
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