An efficient approach to nowcasting the time-varying reproduction number

Abstract

Estimating the instantaneous reproduction number (ℛt) in near real-time is crucial for monitoring and responding to epidemic outbreaks on a daily basis. However, such estimates often suffer from bias due to reporting delays inherent in surveillance systems. A fast and flexible Bayesian methodology is proposed to overcome this challenge by estimatingℛtwhile taking into account reporting delays. Furthermore, the uncertainty associated with the nowcasting of cases is naturally taken into account to get a valid uncertainty estimation of the nowcasted reproduction number. The proposed methodology is evaluated through a simulation study and applied to COVID-19 incidence data in Belgium.