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Flattening the curve: Insights from queueing theory.

Sergio Palomo¹, Jamol J Pender^1,2, William A Massey³

¹Cornell University Systems Engineering, Ithaca, NY, United States of America.

|June 16, 2023

Summary

Flattening the curve through social distancing can significantly reduce peak hospital demand during pandemics like coronavirus. This strategy helps healthcare systems manage patient influx and avoid unnecessary fatalities.

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Published on: January 9, 2016

Area of Science:

Epidemiology
Mathematical Modeling
Public Health

Background:

The coronavirus pandemic, originating in Wuhan, China in 2019, has spread globally, causing significant concern for healthcare systems worldwide.
The United States faces potential healthcare system overload due to a rapid influx of coronavirus patients, necessitating understanding of disease impact.
Mitigation strategies, including social distancing to "flatten the curve," are being implemented to decrease new infection rates.

Purpose of the Study:

To analyze the impact of "flattening the curve" on peak hospital resource demand using queueing theory.
To quantify the necessary aggressiveness of societal policies to prevent healthcare system overload.
To examine how curve flattening affects the time lag between peak hospitalizations and peak resource demand.

Main Methods:

Utilizing queueing theoretic methods to model the time evolution of coronavirus hospitalizations.
Employing a dynamical system based on infinite server queues with time-inhomogeneous Poisson arrival rates.
Analyzing empirical data from Italy and the United States to validate model insights.

Main Results:

The study quantifies the effect of "flattening the curve" on peak hospital resource demand.
It characterizes the required policy aggressiveness to prevent healthcare system capacity from being overwhelmed.
The analysis demonstrates the impact of curve flattening on the time lag between peak hospitalizations and peak resource demand.

Conclusions:

"Flattening the curve" is a critical strategy for managing healthcare resources during a pandemic.
Queueing theory provides a valuable framework for understanding and predicting pandemic-related healthcare demands.
Societal policies aimed at reducing infection rates are essential for maintaining healthcare system stability and reducing mortality.