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A topological data analysis approach
to the epidemiology of Influenza
Abstract. Influenzanet is a system to monitor the activity of influenza-like-illness [ILI] with the aid of internet volunteers. Topological data analysis [TDA] examines the structure of data and contributes to the development of medicine, studying properties of a continuous space by the analysis of a discrete sample of it. Using TDA we analyze the topology of Influenzanet data identifying noise and distinguishing higher dimension features. This is done both in terms of the overall structure of a disease as well as its evolution. It provides a way to test agreement at a global scale arising from standard local models. We also compare this qualitative method to other quantitative methods such as Fourier analysis or dynamical time warping [DTW].
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