Strategies evaluation in environmental conditions by symbolic data analysis: application in medicine and epidemiology to trachoma

Christiane Guinot (), Denis Malvy (), Jean-François Schémann (), Filipe Afonso (), Raja Haddad () and Edwin Diday ()

Advances in Data Analysis and Classification, 2015, vol. 9, issue 1, 107-119

Abstract: Trachoma, caused by repeated ocular infections with Chlamydia trachomatis whose vector is a fly, is an important cause of blindness in the world. We are presenting here an application of the Symbolic Data Analysis approach to an interventional study on trachoma conducted in Mali. This study was conducted to choose among three antibiotic strategies those with the best cost-effectiveness ratio and to find the demographic and environmental parameters on which we could try to intervene. The Symbolic Data Analysis approach aims at studying classes of individuals considered as new units. These units are described by variables whose values express for each class the variation of the values taken by each of its individuals. Finally, the results obtained are compared to those previously provided by multiple logistic regression analysis. Symbolic Data Analysis actually provides a new perspective on this study and suggests that some demographic, economics and environmental parameters are related to the disease and its evolution during the treatment, whatever the strategy. Moreover, it is shown that the efficiency of each strategy depends on environmental parameters. Copyright Springer-Verlag Berlin Heidelberg 2015

Keywords: Symbolic Data Analysis; Multiple logistic regression; Trachoma; 62-07; 62-09 (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s11634-015-0201-2

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