Nowcasting COVID-19 incidence indicators during the Italian first outbreak.

Authors :: Alaimo Di Loro P
Divino F
Farcomeni A
Jona Lasinio G
Lovison G
Maruotti A
Mingione M
Source :: Statistics in medicine [Stat Med] 2021 Jul 20; Vol. 40 (16), pp. 3843-3864. Date of Electronic Publication: 2021 May 06.
Publication Year :: 2021
Abstract: A novel parametric regression model is proposed to fit incidence data typically collected during epidemics. The proposal is motivated by real-time monitoring and short-term forecasting of the main epidemiological indicators within the first outbreak of COVID-19 in Italy. Accurate short-term predictions, including the potential effect of exogenous or external variables are provided. This ensures to accurately predict important characteristics of the epidemic (e.g., peak time and height), allowing for a better allocation of health resources over time. Parameter estimation is carried out in a maximum likelihood framework. All computational details required to reproduce the approach and replicate the results are provided.<br /> (© 2021 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.)