Analysis of Hospital Bed Requirements Using Discrete Event Simulation and Mathematical Modeling

TL;DR

This paper uses discrete event simulation and mathematical modeling to analyze hospital bed requirements, demonstrating model stability across scenarios and validating results against established systems like the Machine Repair Problem and Erlang-Loss System.

Contribution

It introduces a combined simulation and mathematical approach to evaluate hospital bed needs and validates the model against classical queuing systems.

Findings

Model reaches steady-state in all scenarios

Simulation results are consistent across different initial conditions

Model validated against known queuing systems

Abstract

Using SimPy and Discrete Event Simulation we have observed the different model responses of a system consisting of a hospital and people getting sick/healing under different initial conditions. In our model, each independent person can get sick at an exponential rate. The hospital's capacity is limited and accepts only a limited amount of sick people. When the hospital gets full, people are sent home to heal. This is simulated under different conditions and the simulation results have demonstrated that the model reaches the steady-state in every scenario. These cause the outputs of the simulation to be similar to each other even when the simulation is run with different initial conditions. The results are compared with the Machine Repair Problem and Erlang-Loss System and the model is validated.