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Decision Making Environment on Rift Valley Fever in Ferlo (Senegal)

Decision Making Environment on Rift Valley Fever in Ferlo (Senegal) The Rift Valley fever (RVF), which first appeared in Kenya in 1912, is an anthropozoonosis widespread in tropical areas. In Senegal, it is particularly felt in the Ferlo area where a strong presence of ponds shared by humans, cattle and vectors is noted. As part of the studies carried out on the environmental factors which favour its start and propagation, the focus of this paper is put on the decision making process to evaluate the impacts, the interactions and to make RVF monitoring easier. The present paper proposes a model based on data mining techniques and dedicated to trade experts. This model integrates all the involved data and the results of the analyses made on the characteristics of the surrounding ponds. This approach presents some advantage in revealing the relationship between environmental factors and RVF transmission vectors for space–time epidemiology monitoring purpose. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Acta Biotheoretica Springer Journals

Decision Making Environment on Rift Valley Fever in Ferlo (Senegal)

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References (6)

Publisher
Springer Journals
Copyright
Copyright © 2014 by Springer Science+Business Media Dordrecht
Subject
Philosophy; Philosophy of Biology; Evolutionary Biology
ISSN
0001-5342
eISSN
1572-8358
DOI
10.1007/s10441-014-9235-7
pmid
25107274
Publisher site
See Article on Publisher Site

Abstract

The Rift Valley fever (RVF), which first appeared in Kenya in 1912, is an anthropozoonosis widespread in tropical areas. In Senegal, it is particularly felt in the Ferlo area where a strong presence of ponds shared by humans, cattle and vectors is noted. As part of the studies carried out on the environmental factors which favour its start and propagation, the focus of this paper is put on the decision making process to evaluate the impacts, the interactions and to make RVF monitoring easier. The present paper proposes a model based on data mining techniques and dedicated to trade experts. This model integrates all the involved data and the results of the analyses made on the characteristics of the surrounding ponds. This approach presents some advantage in revealing the relationship between environmental factors and RVF transmission vectors for space–time epidemiology monitoring purpose.

Journal

Acta BiotheoreticaSpringer Journals

Published: Aug 9, 2014

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