Nowcasting COVID?19 incidence indicators during the Italian first outbreak

A novel parametric regression model is proposed to fit incidence data typically collected during epidemics. The proposal motivated by real-time monitoring and short-term forecasting of the main epidemiological indicators within first outbreak COVID-19 in Italy. Accurate predictions, including potential effect exogenous or external variables are provided. This ensures accurately predict important characteristics epidemic (e.g., peak time height), allowing for a better allocation health resources over time. Parameter estimation carried out maximum likelihood framework. All computational details required reproduce approach replicate results