Networks and Spatial Economics

, Volume 17, Issue 4, pp 1137–1159 | Cite as

Identifying Critical Components of a Public Transit System for Outbreak Control

  • András Bóta
  • Lauren M. Gardner
  • Alireza Khani


Modern public transport networks provide an efficient medium for the spread of infectious diseases within a region. The ability to identify components of the public transit system most likely to be carrying infected individuals during an outbreak is critical for public health authorities to be able to plan for outbreaks, and control their spread. In this study we propose a novel network structure, denoted as the vehicle trip network, to capture the dynamic public transit ridership patterns in a compact form, and illustrate how it can be used for efficient detection of the high risk network components. We evaluate a range of network-based statistics for the vehicle trip network, and validate their ability to identify the routes and individual vehicles most likely to spread infection using simulated epidemic scenarios. A variety of outbreak scenarios are simulated, which vary by their set of initially infected individuals and disease parameters. Results from a case study using the public transit network from Twin Cities, MN are presented. The results indicate that the set of transit vehicle trips at highest risk of infection can be efficiently identified, and are relatively robust to the initial conditions of the outbreak. Furthermore, the methods are illustrated to be robust to two types of data uncertainty, those being passenger infection levels and travel patterns of the passengers.


Network modeling Public transportation Infection models Outbreak control Public health 



We thank the National Health and Medical Research Council (NHMRC) for funding, project grant (No. APP1082524). The contents of the published material are solely the responsibility of the Administering Institution, a Participating Institution or individual authors and do not reflect the views of the NHMRC.


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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Research Centre for Integrated Transport Innovation, School of Civil and Environmental EngineeringUniversity of New South Wales (UNSW) AustraliaSydneyAustralia
  2. 2.Department of Civil, Environmental and Geo- EngineeringUniversity of Minnesota Twin CitiesMinneapolisUSA

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