  The time varying reproduction number R is a critical variable for situational
awareness during infectious disease outbreaks, but delays between infection and
reporting hinder its accurate estimation in real time. We propose a nowcasting
method for improving the timeliness and accuracy of R estimates, based on
comparisons of successive versions of surveillance databases. The method was
validated against COVID-19 surveillance data collected in Italy over an
18-month period. Compared to traditional methods, the nowcasted reproduction
number reduced the estimation delay from 13 to 8 days, while maintaining a
better accuracy. Moreover, it allowed anticipating the detection of periods of
epidemic growth by between 6 and 23 days. The method offers a simple and
generally applicable tool to improve situational awareness during an epidemic
outbreak, allowing for informed public health response planning.
