An Artificial Immune System Approach for a Multi-compartment Queuing Model for Improving Medical Resources and Inpatient Bed Occupancy in Pandemics

Abstract

In the context of the Covid-19 pandemic the pressure that is put on the medical systems is increasing exponentially. Healthcare systems resources are in general scarce, and hence they require policies that ensure the optimal usage of beds and utilization costs. The aim of this study is to explore how artificial immune system approaches for a multi-queuing model may aid the hospital managers improve their resources. The proposed system outlines the route of Covid-19 patients in the intensive care unit (ICU), the compartmental model proposes a reasonable composition of the ICU, considering the queuing parameters, while the artificial immune system optimizes the needed resources (beds plus associated costs). The methodology was demonstrated through a simulation based on real data collected from official sources.

Keywords

• artificial intelligence
• evolutionary computation
• hospitals
• optimization
• queueing analysis