Topological Data Analysis and Covid-19 epidemic dynamics

Conferenciante: Stefanella Boatto (Instituto de Matematica, Universidade Federal do Rio de Janeiro)

Abstract: Data Science is a highly evolving discipline that presents many challenges. For example, in the case of an epidemic, how can we identify which socio-economic and social parameters, tourist mobility, prevention and control measures have the greatest impact on the dynamics of an epidemic? In recent years Topological Data Analysis has proved to be a powerful tool, a lens to highlight some dominant features of collective phenomena and explore large and complex data sets. In this talk we will see a brief introduction and how this new highly multidisciplinary tool - bringing together areas such as Space-Time Analysis, Algebraic Topology, Complex Networks, Linear algebra and Computation- is quite useful to characterise the COVID-19 dynamics. Socio-economical aspects will also be presented.