Cargando…
Forecasting of COVID-19 onset cases: a data-driven analysis in the early stage of delay
The outbreak of COVID-19 has become a global public health event. Many researchers have proposed many epidemiological models to predict the outbreak trend of COVID-19, but all use confirmed cases to predict “onset cases.” In this article, a total of 5434 cases were collected from National Health Com...
Autores principales: | Wang, Xueli, Li, Ying, Jia, Jinzhu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7786867/ https://www.ncbi.nlm.nih.gov/pubmed/33405171 http://dx.doi.org/10.1007/s11356-020-11859-w |
Ejemplares similares
-
Cross-sectional analysis and data-driven forecasting of confirmed COVID-19 cases
por: Jing, Nan, et al.
Publicado: (2021) -
Correcting notification delay and forecasting of COVID-19 data
por: Sarnaglia, Alessandro J.Q., et al.
Publicado: (2022) -
Forecasting COVID-19 pandemic: A data-driven analysis
por: Nabi, Khondoker Nazmoon
Publicado: (2020) -
A Bayesian Approach to Real-Time Monitoring and Forecasting of Chinese Foodborne Diseases
por: Wang, Xueli, et al.
Publicado: (2018) -
Forecasting Covid-19 Dynamics in Brazil: A Data Driven Approach
por: Pereira, Igor Gadelha, et al.
Publicado: (2020)