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In late December 2019, a novel strand of Coronavirus (SARS-CoV-2) causing asevere, potentially fatal respiratory syndrome (COVID-19) was identified inWuhan, Hubei Province, China and is causing outbreaks in multiple worldcountries, soon becoming a pandemic. Italy has now become the most hit countryoutside of Asia: on March 16, 2020, the Italian Civil Protection documented atotal of 27980 confirmed cases and 2158 deaths of people tested positive forSARS-CoV-2. In the context of an emerging infectious disease outbreak, it is ofparamount importance to predict the trend of the epidemic in order to plan aneffective control strategy and to determine its impact. This paper proposes anew epidemic model that discriminates between infected individuals depending onwhether they have been diagnosed and on the severity of their symptoms. Thedistinction between diagnosed and non-diagnosed is important becausenon-diagnosed individuals are more likely to spread the infection thandiagnosed ones, since the latter are typically isolated, and can explainmisperceptions of the case fatality rate and of the seriousness of the epidemicphenomenon. Being able to predict the amount of patients that will developlife-threatening symptoms is important since the disease frequently requireshospitalisation (and even Intensive Care Unit admission) and challenges thehealthcare system capacity. We show how the basic reproduction number can beredefined in the new framework, thus capturing the potential for epidemiccontainment. Simulation results are compared with real data on the COVID-19epidemic in Italy, to show the validity of the model and compare differentpossible predicted scenarios depending on the adopted countermeasures.

A SIDARTHE Model of COVID-19 Epidemic in Italy