Increasing situational awareness through nowcasting of the reproduction number

TL;DR

This paper introduces a nowcasting method that enhances the timeliness and accuracy of the reproduction number R during infectious disease outbreaks, enabling earlier detection of epidemic growth and better situational awareness.

Contribution

The paper presents a novel nowcasting approach that improves real-time estimation of R by comparing successive surveillance data versions, validated with COVID-19 data from Italy.

Findings

Reduced estimation delay from 13 to 8 days

Anticipated epidemic growth detection by 6 to 23 days

Maintained better accuracy than traditional methods

Abstract

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.