Chinese and Italian COVID-19 outbreaks can be correctly described by a modified SIRD model

Diego Caccavo

Unfortunately, these measures were not able to stop the spreading of SARS-CoV-2, which caused several outbreaks around the globe. These drastic measures, also adopted by other EU countries, apart from the health sector, have a dramatic impact on the global economy as well as on the lifestyle habits of millions of people. Epidemiologic descriptions and predictions could help in the understanding of the dynamic of the COVID-19 disease, supporting governments and health authorities in the resources allocation [5] . Most of the models proposed until now to describe the COVID-19 outbreaks, due to the scarcely data available of a still ongoing epidemic, are heuristic models. These models are "fitting" equation, exponential [5] or logistic [6] , used to describe the infection data, whose parameters have scarce (or none) physical meaning and their use for prediction, especially at long term, should be avoided. On the contrary compartmental models could constitute the right trade-off between the need of having physical based parameters, the easiness of solution and the scarce presence of data in the evolving epidemic. Typically, the population of interest is subdivided into a small number of compartments based on infection status (e.g. susceptible, infectious or recovered) and the flows between these compartments are described by ordinary differential equations [7] . Aim of this work is to develop a compartmental model (SIRD) to describe first the Chinese COVID-19 epidemic and then, by perturbation of the model parameters, to describe and predict the Italian COVID-19 epidemic.