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

Balveer Saini, Dharamender Singh and Kailash Chand Sharma

Journal of Management World, 2025, vol. 2025, issue 1, 718-727

Abstract: Pandemics are life-threatening and resource-intensive. Hospitals with limited resources saw a surge in patients during pandemics. These situations can result in a large number of casualties in a small time period. The “golden hour†after infection is crucial for treatment and can significantly impact the survival rate. It is inevitable to treat these victims in the “golden hour†to prevent serious loss of lives. Our objective is to enhance the capacity of the healthcare system to treat victims in "golden hours" during pandemics. This article will evaluate the arrival of victims and compare it with the hospital's treatment capabilities. We have created a system known as the "Transient Act System (TAS)." This system identifies overcrowding in hospitals. The M/M/s/GD/c/∞ type multi-channel queueing system is described to calculate the hospital treatment capacity. The hospital capacity calculation method is based on the waiting time probability distribution function, where the patient waiting times follow an Erlang distribution. The suggested method is validated using numerical analysis, including probability distribution and graphical representations. The study ends with suggestions for future research and advice on how to increase the effectiveness of the hospital system in pandemic situations. This study serves as an example that justifies the feasibility. The findings of this study can immediately help policymakers and planners make better decisions about pandemic situations and future health crises.

Keywords: COVID-19 Pandemic; Erlang distribution; Hospitals Treatment Capability; Multi-Server Queueing Model; Priority Queue; Transient Act System. (search for similar items in EconPapers)
Date: 2025
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