Thomas Bartz-Beielstein, Marcel Droescher, Alpar Guer, Alexander Hinterleitner, Tom Lawton, Olaf Mersmann, Dessislava Peeva, Lennard Reese, Frederik Rehbach, Nicolas Rehbach, Amrita Sen, Aleksandr Subbotin and Martin Zaefferer
Hospitals and health-care institutions need to plan the resources required for
handling the increased load, i.e., beds and ventilators during the COVID-19
BaBSim.Hospital, an open-source tool for capacity planning based on discrete
event simulation, was developed over the last year to support doctors,
administrations, health authorities, and crisis teams in Germany.
To obtain reliable results, 29 simulation parameters such as durations and
probabilities must be specified. While reasonable default values were obtained
in detailed discussions with medical professionals, the parameters have to be
regularly and automatically optimized based on current data.
We aim to investigate how a set of parameters that is tailored to the German
health system can be transferred to other regions. Therefore, we will use data
from the UK. Our study demonstrates the flexibility of the discrete event
simulation approach. However, transferring the optimal German parameter settings
to the UK situation does not work—parameter ranges must be modified. The
adaptation has been shown to reduce simulation errors by nearly 70%.
The simulation-via-optimization approach is not restricted to health-care
institutions, it is applicable to many other real-world problems, e.g., the
development of new elevator systems to cover the last mile or simulation of
student flow in academic study periods.
Link to the simulator:
Link to the open-source software: