Several compartmental models have been designed in epidemiology to simplify the mathematical modeling of infectious diseases, so as to describe their spreading in a population of individuals. Among them, we will make use here of the SEIAR that expands the basic SIR model and the SEIR one. The choice of SEIAR model is due to the fact that we wish to estimate here the spreading of the coronavirus COVID-19 in Italy. In fact, several papers have stressed the issue that for this pandemic, the number of asymptomatic infectious subjects is very high. Given that asymptomatic subjects are obviously not contained in official figures, their presence causes a much wider and longer spread of this disease, with more infectious people. Moreover, an important remark on the use of the SEIAR model is that the basic reproduction number R0 it computes is much higher than that provided by the use of SIR and SEIR models.
Differential evolution to estimate the parameters of a SEIAR model with dynamic social distancing: the case of COVID-19 in Italy
I De Falco;U Scafuri;E Tarantino
2021
Abstract
Several compartmental models have been designed in epidemiology to simplify the mathematical modeling of infectious diseases, so as to describe their spreading in a population of individuals. Among them, we will make use here of the SEIAR that expands the basic SIR model and the SEIR one. The choice of SEIAR model is due to the fact that we wish to estimate here the spreading of the coronavirus COVID-19 in Italy. In fact, several papers have stressed the issue that for this pandemic, the number of asymptomatic infectious subjects is very high. Given that asymptomatic subjects are obviously not contained in official figures, their presence causes a much wider and longer spread of this disease, with more infectious people. Moreover, an important remark on the use of the SEIAR model is that the basic reproduction number R0 it computes is much higher than that provided by the use of SIR and SEIR models.File | Dimensione | Formato | |
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Descrizione: Differential evolution to estimate the parameters of a SEIAR model with dynamic social distancing: the case of COVID-19 in Italy
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