A Queueing Theory Approach to Analyze the Impact of COVID-19 Pandemic on Hospitals System Capabilities: A Lesson for Future Pandemic Preparedness

Abstract

Pandemics are life-threatening and resource-intensive events. Hospitals with limited resources experience a surge in patients during such crises. These situations can lead to a high number of casualties within a short period. The "golden hour" after infection is critical for treatment and can significantly influence survival rates. It is essential to treat victims within this timeframe to prevent serious loss of life. Our goal is to improve the capacity of healthcare systems to treat victims during the golden hours in pandemics. This article evaluates patient arrivals and compares them with hospital treatment capabilities. We have developed a system called the Transient Act System (TAS), which detects hospital overcrowding. The hospital's treatment capacity is modeled using an M/M/s/GD/c/ multi-channel queueing system to estimate patient handling capabilities. Capacity calculations are based on the waiting time probability distribution function, with patient waiting times following an Erlang distribution. The proposed method has been validated through numerical analysis, including probability distributions and graphical representations. The study concludes with recommendations for future research and strategies to enhance hospital efficiency during pandemics. This research demonstrates the feasibility of the approach. The findings can assist policymakers and healthcare planners in making informed decisions during health crises, ultimately improving response effectiveness and saving lives.