Forecasting hospital demand in metropolitan areas during the current COVID-19 pandemic and estimates of lockdown-induced 2nd waves.
We present a forecasting model aim to predict hospital occupancy in metropolitan areas during the current COVID-19 pandemic. Our SEIRD type model features asymptomatic and symptomatic infections with detailed hospital dynamics. We model explicitly branching probabilities and non-exponential residenc...
Main Authors: | Marcos A Capistran, Antonio Capella, J Andrés Christen |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2021-01-01
|
Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0245669 |
Similar Items
-
Filtering and improved Uncertainty Quantification in the dynamic estimation of effective reproduction numbers
by: Marcos A. Capistrán, et al.
Published: (2022-09-01) -
Bayesian sequential data assimilation for COVID-19 forecasting
by: Maria L. Daza-Torres, et al.
Published: (2022-06-01) -
COVID-19 Pandemic: Impacts on Air Quality during Partial Lockdown in the Metropolitan Area of São Paulo
by: Débora Souza Alvim, et al.
Published: (2023-02-01) -
Simultaneous estimation of the supply and demand for household location in a multizoned metropolitan area
by: Bradbury, Katharine L., et al.
Published: (2011) -
Estimation of the price elasticity of demand acting metropolitan producers
by: Engle, Robert Fry
Published: (2011)