Geometry and topology of periodically correlated processes : Analysis of the variability of seasonal pediatric epidemics
Each year emergency department are faced with epidemics that affect their organisation and deteriorate the quality of the cares. The analyse of these outbreak is tough due to their huge variability. We aim to study these phenomenon and to bring out a new paradigm in the analysis of their behavior. With this aim in mind, we propose to tackle this problem through geometry and topology: the variability process being periodically correlated, the theory of dilation exhibit a set of matrices that carry all the information about this process. This set of matrices allow to map the process into a Lie group, defined as the set of all curves on a manifold. Thus, it is possible to compare stochastic processes using properties of Lie groups. Then, we consider the point cloud formed by the set of dilation matrices, to gain more intuitions about the underlying process. We proved a relation between the temporal aspect of the signal and the structure of the set of its dilation matrices. We used and developped persistent homology tools, and were able to classify non-stationary processes. Eventually, we implement these techniques directly on the process of arrivals to detect the trigger of the epidemics. Overall we established a complete and a coherent framework, both theoretical and practical.
KEYWORDS : Applied Mathematics, stochastic geometry, Topology, Lie group, lineaér approximation, expansion matrix