Identifying Critical Components of a Public Transit System for Outbreak Control

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