Increasing situational awareness through nowcasting of the reproduction number.
epidemic surveillance
nowcasting
outbreaks
reproduction number
situational awareness
Journal
Frontiers in public health
ISSN: 2296-2565
Titre abrégé: Front Public Health
Pays: Switzerland
ID NLM: 101616579
Informations de publication
Date de publication:
2024
2024
Historique:
received:
10
05
2024
accepted:
05
08
2024
medline:
5
9
2024
pubmed:
5
9
2024
entrez:
5
9
2024
Statut:
epublish
Résumé
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.
Sections du résumé
Background
UNASSIGNED
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
UNASSIGNED
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
UNASSIGNED
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
UNASSIGNED
Nowcasting augments epidemic awareness, empowering better informed public health responses.
Identifiants
pubmed: 39234082
doi: 10.3389/fpubh.2024.1430920
pmc: PMC11371679
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1430920Informations de copyright
Copyright © 2024 Bizzotto, Guzzetta, Marziano, Del Manso, Mateo Urdiales, Petrone, Cannone, Sacco, Poletti, Manica, Zardini, Trentini, Fabiani, Bella, Riccardo, Pezzotti, Ajelli and Merler.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.