This study reports modelling of the impact of population-wide interventions in Italy on COVID-19 epidemic. The authors propose a new algorithm for predicting the impact of control measures on spread of infection based on data acquired from the field during the Italian outbreak; it includes the potential for transmission from asymptomatic as well as symptomatic cases.

The model considers eight stages of infection: susceptible (S), infected (I), diagnosed (D), ailing (A), recognized (R), threatened (T), healed (H) and extinct (E), collectively termed SIDARTHE. They compare simulation results with real data on the COVID-19 epidemic in Italy, and model possible scenarios of implementation of countermeasures. Their results demonstrate that restrictive social-distancing measures will need to be combined with widespread testing and contact tracing to end the ongoing COVID-19 pandemic.

They also emphasize that, once the outbreak is controlled, rigorous regular testing of the population with quarantining of detected cases (all asymptomatic and symptomatic) AND of their close contacts over the period of infectivity will be needed to prevent a new epidemic outbreak