# Modelling the spread of infectious diseases in public transport systems under varying demand patterns and capacity constraints

## TL;DR

This paper studies how public transport can reduce disease spread by adjusting passenger capacity and demand, balancing health and service efficiency.

## Contribution

The study introduces a model combining demand and capacity measures to minimize disease spread in public transport while maintaining operability.

## Key findings

- Restricting vehicle capacity significantly reduces infection spread.
- Demand-related measures have a stronger effect than capacity restrictions.
- Combining capacity and demand measures offers optimal solutions for public health and transport operability.

## Abstract

Understanding the dynamics of passenger interactions and their epidemiological impact across public transportation systems is crucial for both service efficiency and public health. High passenger density and close physical proximity have 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 the spread of the disease. One of these measures was introducing spacing and capacity constraints on public transit vehicles. Our objective is to explore the effects of changes in demand and transportation measures from an epidemiological point of view, offering alternative measures to public transportation companies to keep the system operational while minimizing the epidemiological risk as much as possible. Our findings show that restricting vehicle capacity can significantly reduce the spread of infections, while demand-related measures have an even stronger effect. Combining these approaches offers the best solutions for balancing public health and operability.