In this project we tried to get an overview of the current state of the SARS-Cov-2 virus, focusing on the spread of the Covid-19 disease which led many countries to a complete lockdown, forcing people into a quarantine state and many activities to shut down their operations.
The dataset provided contains information about the cumulative number of Covid-19 cases, deaths and recovered people across the world, up to the 22Nd of March. The goal of the analysis is to build a model able to provide a relatively long term overview of the trend of the virus spread and a more accurate prediction in the short term, mainly focusing on single countries, since the different countermeasures taken and different specific factors involved make a solid case to consider each country individually. Our modeling strategy is based on two different approaches: a theory-based, parametric approach and a data-centric approach. The former can give a general overview and a long term estimation, whereas the second is suitable for more accurate short term predictions and fit.