01624572

Component

Identifying components of the public transit system most likely to exacerbate disease spread is critical for public health authorities to be able to plan for epidemics and control their spread. In this work the authors propose a method to detect such components in a transit network using a three-stage approach. They first use results from a transit simulation model to generate a contact network that is representative of the potential physical encounters between passengers. They then design and run a variety of epidemic scenarios atop this network which vary in their set of initially infected individuals, and properties of the disease. The expected spread (and variance) of the outbreak in terms of the infected passenger set are compared across scenarios. The infected passenger sets are then used to identify the vehicle trips most likely to transport infected passengers during an epidemic, which represent optimal locations to implement vehicle surveillance. Results from a case study using the public transit network from Austin, TX are presented. The authors show that the infection scenarios vary substantially in the pattern of spread at the individual level, but the set of transit vehicle trips at highest risk of infection is robust to the initial conditions of the outbreak.

This paper was sponsored by TRB committee ABR10 Standing Committee on Critical Transportation Infrastructure Protection.

01618707

17-01455

English

20p

2017

Transportation Research Board 96th Annual Meeting

Digital/other

Figures; References; Tables

Communicable diseases; Decision support systems; Epidemiology; Public health; Public transit; Transit riders

Epidemics; Infections

Austin (Texas)

Planning and Forecasting; Public Transportation; Safety and Human Factors; Security and Emergencies

Transportation Research Board Annual Meeting 2017 Paper #17-01455

PRP, TRIS, TRB, ATRI

Dec 8 2016 10:28AM