Qualitative forecast and temporal evolution of the disease spreading using a simplified model and COVID-19 data for Italy

Abstract

AbstractIn a previous paper [1] a simplified SEIR model applied to COVID-19 cases detected in Italy, including the lockdown period, has shown a good fitting to the time evolution of the disease during the observed period.In this paper that model is applied to the initial data available for Italy in order to forecast, in a qualitative way, the time evolution of the disease spreading. The values obtained are to be considered indicative.The same model has been applied both to the data relating to Italy and to some italian regions generally finding good qualitative results.The only tuning parameter in the model is the ‘incubation period’ τ.In this modelization the tuning parameter, together with the calculated growth rate of the exponential curve used to approximate the early stage data, are in strong relationship with the compartments’ transfer rates.The relationships between the parameters simplify modeling by allowing a rough (not supported by statistical considerations) forecast of the time evolution, starting from the first period of growth of the diffusion.ConclusionsA simplified compartmental model that uses only the incubation period and the exponential growth rate as parameters is applied to the COVID-19 data for Italy in several periods of the initial growth of the diffusion showing the different stages of the spread evolution. The simplification is based on the strong protection measures that were in place in Italy during the lockdown period after the initial free diffusion.