The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/0041578f-5dd9-46d2-ad41-19ac36d7f1a5

Baas, Stef (2024): Simulation data for paper Dynamic fair balancing of COVID-19 patients over hospitals based on forecasts of bed occupancy. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/0041578f-5dd9-46d2-ad41-19ac36d7f1a5.v1

Usage statistics

Categories

• Applied Mathematics
• Mathematical Sciences

Keywords

Bed occupancy Corona COVID-19 Load balancing Patient allocation Queueing theory regions Stochastic program

Licence

CC BY-NC-SA 4.0

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by Stef Baas

Simulation data of patient reallocation over hospitals or regions. Research objective: determining the benefits of regional re-allocation of COVID-19 patients using stochastic approximation and stochastic programming, type of research: simulation study, method of data collection: simulations, type of data: R datasets

History

• 2024-06-24 first online, published, posted

Publisher

4TU.ResearchData

Format

.rds files

Associated peer-reviewed publication

Dynamic fair balancing of COVID-19 patients over hospitals based on forecasts of bed occupancy

Organizations

University of Twente, Center for Healthcare Operations Improvement and Research (CHOIR)