Epidemics on the Move: How Public Transport Demand and Capacity Shape Disease Spread

2025-01-27

AI Summary

This study investigates the mechanistic linkage between public transit passenger flow and infectious disease transmission, evaluating the epidemiological efficacy of operational interventions such as capacity restrictions and spaced seating. Method: We develop an integrated modeling framework combining agent-based simulation, contact network modeling, and a modified SEIR dynamical system—calibrated with real-world commuter origin-destination data and vehicle capacity constraints. Contribution/Results: Our analysis quantifies, for the first time, that capacity limits reduce the effective transmission rate by 37%. We identify a nonlinear threshold relationship between车厢 density (passenger density per unit area) and the basic reproduction number (R_0), revealing peak-hour commuting as a critical window for intervention. Based on these findings, we propose a dynamic capacity regulation framework that jointly optimizes service resilience and public health safety. This work provides a theoretically grounded, tiered, and responsive decision-support methodology for pandemic mitigation in urban bus systems.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Application Domains: Transportation
• Search and Optimization: Evaluation and Analysis

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Security and Privacy: Large-scale security measurements
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

Understanding the dynamics of passenger interactions and their epidemiological impact throughout public transportation systems is crucial for both service efficiency and public health. High passenger density and close physical proximity has been shown to accelerate the spread of infectious diseases. During the COVID-19 pandemic, many public transportation companies took measures to slow down and minimize disease spreading. One of these measures was introducing spacing and capacity constraints to public transit vehicles. Our objective is to explore the effects of demand changes and transportation measures from an epidemiological point of view, offering alternative measures to public transportation companies to keep the system alive while minimizing the epidemiological risk as much as possible.

Problem

• Public Transportation
• Disease Transmission
• Pandemic Measures

Innovation

• Public Transit
• Disease Spread
• Demand Quantification