Modeling Epidemic Spreading through Public Transit using Time-Varying Encounter Network
arXiv:2004.04602
Abstract
Passenger contact in public transit (PT) networks can be a key mediate in the spreading of infectious diseases. This paper proposes a time-varying weighted PT encounter network to model the spreading of infectious diseases through the PT systems. Social activity contacts at both local and global levels are also considered. We select the epidemiological characteristics of coronavirus disease 2019 (COVID-19) as a case study along with smart card data from Singapore to illustrate the model at the metropolitan level. A scalable and lightweight theoretical framework is derived to capture the time-varying and heterogeneous network structures, which enables to solve the problem at the whole population level with low computational costs. Different control policies from both the public health side and the transportation side are evaluated. We find that people's preventative behavior is one of the most effective measures to control the spreading of epidemics. From the transportation side, partial closure of bus routes helps to slow down but cannot fully contain the spreading of epidemics. Identifying "influential passengers" using the smart card data and isolating them at an early stage can also effectively reduce the epidemic spreading.
References in corpus (18)
- Understanding individual human mobility patterns
- Epidemic processes in complex networks
- Identification of influential spreaders in complex networks
- Multiscale mobility networks and the large scale spreading of infectious diseases
- Prediction and predictability of global epidemics: the role of the airline transportation network
- Forecast and Control of Epidemics in a Globalized World
- A High-Resolution Human Contact Network for Infectious Disease Transmission
- k-core organization of complex networks
- The fundamental advantages of temporal networks
- Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees
- Small vulnerable sets determine large network cascades in power grids
- Absence of influential spreaders in rumor dynamics
- Understanding metropolitan patterns of daily encounters
- Percolation and Epidemic Thresholds in Clustered Networks
- Random walks and search in time-varying networks
- The k-core as a predictor of structural collapse in mutualistic ecosystems
- Collapse of Resilience Patterns in Generalized Lotka-Volterra Dynamics and Beyond
- Scaling of contact networks for epidemic spreading in urban transit systems