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Increasing situational awareness through nowcasting of the reproduction number.


ABSTRACT: The time-varying reproduction number R is a critical variable for situational awareness during infectious disease outbreaks; however, delays between infection and reporting of cases hinder its accurate estimation in real-time. A number of nowcasting methods, leveraging available information on data consolidation delays, have been proposed to mitigate this problem. In this work, we retrospectively validate the use of a nowcasting algorithm during 18 months of the COVID-19 pandemic in Italy by quantitatively assessing its performance against standard methods for the estimation of R. Nowcasting significantly reduced the median lag in the estimation of R from 13 to 8 days, while concurrently enhancing accuracy. Furthermore, it allowed the detection of periods of epidemic growth with a lead of between 6 and 23 days. Nowcasting augments epidemic awareness, empowering better informed public health responses.

SUBMITTER: Bizzotto A 

PROVIDER: S-EPMC11371679 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature

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<h4>Background</h4>The time-varying reproduction number R is a critical variable for situational awareness during infectious disease outbreaks; however, delays between infection and reporting of cases hinder its accurate estimation in real-time. A number of nowcasting methods, leveraging available information on data consolidation delays, have been proposed to mitigate this problem.<h4>Methods</h4>In this work, we retrospectively validate the use of a nowcasting algorithm during 18 months of the  ...[more]

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