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
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doi: 10.4121/0041578f-5dd9-46d2-ad41-19ac36d7f1a5
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
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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
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)
DATA
files (2)
- 1,608 bytesMD5:
70313b9ce1cfe1665be09061ace258ad
README.txt - 2,507,919,549 bytesMD5:
ada155fa28d5a7dec57cfe8a53f51af2
Simulation data of patient reallocation over hospitals or regions.zip -
download all files (zip)
2,507,921,157 bytes unzipped