Abstract
Over the past few decades, our world has experienced the emergence, or the re-emergence, of several infectious diseases in connection with our fast-changing environment. An example of these emerging diseases is the resurgence of dengue. Dengue is a human arboviral disease, which is mainly transmitted by Aedes mosquitoes. It has been estimated that 50 to 100 million people each year suffer from dengue and that two fifths of the human population are at risk. We have previously showed that the dengue epidemics can be influenced by large climatic oscillations but the associations between dengue cases and climatic factors appear transient underlying the importance of the nonstationary aspect of these epidemics. Here I will extend our previous results by incorporating the spatial dimension of the disease propagation. I will explore different approaches for taking account both the spatial dimension of the observed patterns and the nonstationary nature of the phenomena underlying to dengue epidemics: wavelet decomposition, independent components analysis and generalized mutual entropy. The understanding of the spatio-temporal patterns of disease transmission is of fundamental importance for predicting the patterns of emerging epidemics in our changing world. These preliminary analyses will facilitate the development of models that describe the interactions of different factors on the transmission of the dengue virus.
Bernard Cazelles
Ecology and Evolution, UMR 7625, UPMC-ENS-CNRS, Ecole Normale Supérieure, 46 rue d'Ulm, 75230 Paris Cedex 05, France.
UMMISCO, UMI 209, IRD-UPMC, 93142 Bondy, France