Evidence map›Paper›PMID 39234082›Full record

ArticleFrontiers in public health2024

Increasing situational awareness through nowcasting of the reproduction number.

Andrea Bizzotto, Giorgio Guzzetta, Valentina Marziano, Martina Del Manso, Alberto Mateo Urdiales, Daniele Petrone, Andrea Cannone, Chiara Sacco, Piero Poletti, Mattia Manica and 8 more

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Andrea Bizzotto *Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy.
Giorgio Guzzetta *Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy.
Valentina MarzianoCenter for Health Emergencies, Bruno Kessler Foundation, Trento, Italy.
Martina Del MansoDepartment of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy.
Alberto Mateo UrdialesDepartment of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy.
Daniele PetroneDepartment of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy.
Andrea CannoneDepartment of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy.
Chiara SaccoDepartment of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy.
Piero PolettiCenter for Health Emergencies, Bruno Kessler Foundation, Trento, Italy.
Mattia ManicaCenter for Health Emergencies, Bruno Kessler Foundation, Trento, Italy.
Agnese ZardiniCenter for Health Emergencies, Bruno Kessler Foundation, Trento, Italy.
Filippo TrentiniCovid Crisis Lab, Bocconi University, Milan, Italy.
Massimo FabianiDepartment of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy.
Antonino BellaDepartment of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy.
Flavia RiccardoDepartment of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy.
Patrizio PezzottiDepartment of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy.
Marco AjelliLaboratory for Computational Epidemiology and Public Health, Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, United States.
Stefano MerlerCenter for Health Emergencies, Bruno Kessler Foundation, Trento, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: 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. Methods: 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. Results: 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. Conclusions: Nowcasting augments epidemic awareness, empowering better informed public health responses.

Indexed as

COVID-19AlgorithmsAwarenessBasic Reproduction NumberHumansItalyPandemicsRetrospective StudiesSARS-CoV-2epidemic surveillancenowcastingoutbreaksreproduction numbersituational awareness

Identifiers

PMID39234082
PMCPMC11371679

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.