COVID-19: a simple statistical model for predicting intensive care unit load in exponential phases of the disease
Abstract One major bottleneck in the ongoing COVID-19 pandemic is the limited number of critical care beds. Due to the dynamic development of infections and the time lag between when patients are infected and when a proportion of them enters an intensive care unit (ICU), the need for future intensiv...
Guardado en:
Autores principales: | Matthias Ritter, Derek V. M. Ott, Friedemann Paul, John-Dylan Haynes, Kerstin Ritter |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/b4045b3cd80948ccb49ee74e3696e398 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Risk prediction models for intensive care unit-acquired weakness in intensive care unit patients: A systematic review.
por: Wei Zhang, et al.
Publicado: (2021) -
Some New Simple Inequalities Involving Exponential, Trigonometric and Hyperbolic Functions
por: Bagul,Yogesh J., et al.
Publicado: (2019) -
Intensive Care Unit as a Stressor
por: Mustafa Sahin, et al.
Publicado: (2018) -
Inverted Length-Biased Exponential Model: Statistical Inference and Modeling
por: Waleed Almutiry
Publicado: (2021) -
Intraocular infections in the neonatal intensive care unit
por: Sisk RA, et al.
Publicado: (2012)