Cargando…
Neural network models for influenza forecasting with associated uncertainty using Web search activity trends
Influenza affects millions of people every year. It causes a considerable amount of medical visits and hospitalisations as well as hundreds of thousands of deaths. Forecasting influenza prevalence with good accuracy can significantly help public health agencies to timely react to seasonal or novel s...
Autores principales: | Morris, Michael, Hayes, Peter, Cox, Ingemar J., Lampos, Vasileios |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10491400/ https://www.ncbi.nlm.nih.gov/pubmed/37639427 http://dx.doi.org/10.1371/journal.pcbi.1011392 |
Ejemplares similares
-
The added value of online user-generated content in traditional methods for influenza surveillance
por: Wagner, Moritz, et al.
Publicado: (2018) -
Estimating the secondary attack rate and serial interval of influenza-like illnesses using social media
por: Yom-Tov, Elad, et al.
Publicado: (2015) -
Estimating the Population Impact of a New Pediatric Influenza Vaccination Program in England Using Social Media Content
por: Wagner, Moritz, et al.
Publicado: (2017) -
Providing early indication of regional anomalies in COVID-19 case counts in England using search engine queries
por: Yom-Tov, Elad, et al.
Publicado: (2022) -
Advances in nowcasting influenza-like illness rates using search query logs
por: Lampos, Vasileios, et al.
Publicado: (2015)