Cargando…
Nowcasting by Bayesian Smoothing: A flexible, generalizable model for real-time epidemic tracking
Achieving accurate, real-time estimates of disease activity is challenged by delays in case reporting. “Nowcast” approaches attempt to estimate the complete case counts for a given reporting date, using a time series of case reports that is known to be incomplete due to reporting delays. Modeling th...
Autores principales: | McGough, Sarah F., Johansson, Michael A., Lipsitch, Marc, Menzies, Nicolas A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7162546/ https://www.ncbi.nlm.nih.gov/pubmed/32251464 http://dx.doi.org/10.1371/journal.pcbi.1007735 |
Ejemplares similares
-
Evaluation of Nowcasting for Real-Time COVID-19 Tracking — New York City, March–May 2020
por: Greene, Sharon K., et al.
Publicado: (2020) -
Nowcasting for Real-Time COVID-19 Tracking in New York City: An Evaluation Using Reportable Disease Data From Early in the Pandemic
por: Greene, Sharon K, et al.
Publicado: (2021) -
A machine learning model for nowcasting epidemic incidence
por: Sahai, Saumya Yashmohini, et al.
Publicado: (2022) -
Skilful nowcasting of extreme precipitation with NowcastNet
por: Zhang, Yuchen, et al.
Publicado: (2023) -
Lightning Sensors for Observing, Tracking and Nowcasting Severe Weather
por: Price, Colin
Publicado: (2008)