getIcuBeds

<p>data.frame with obs. of  9 variables</p>

data

<p>Convert the 9 dim DIVI ICU data (bundesland,gemeindeschluessel,..., daten_stand)
into a data.frame with bed, intensiveBedVentilation, and Day</p>

Implements a discrete-event simulation model for a hospital resource planning problem.
The project is motivated by the challenges faced by health care institutions in the current COVID-19 pandemic.
It can be used by health departments to forecast demand for intensive care beds, ventilators, and staff resources.
Our modelling approach is inspired by "A novel modelling technique to predict resource requirements in critical care - a case study" (Lawton and McCooe 2019) and combines two powerful technologies:
(i) discrete event simulation using the 'simmer' package and
(ii) model-based optimization using 'SPOT'.
Ucar I, Smeets B, Azcorra A (2019) <doi:10.18637/jss.v090.i02>.
Bartz-Beielstein T, Lasarczyk C W G, Preuss M (2005) <doi:10.1109/CEC.2005.1554761>.
Lawton T, McCooe M (2019) <doi:10.7861/futurehosp.6-1-17>.

getIcuBeds: getIcuBeds

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