Simulation data for paper Dynamic fair balancing of COVID-19 patients over hospitals based on forecasts of bed occupancy

doi:10.4121/0041578f-5dd9-46d2-ad41-19ac36d7f1a5.v1
The doi 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
Datacite citation style:
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
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

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

DATA

files (2)