About: Modeling Epidemic Spreading through Public Transit using Time-Varying Encounter Network

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Modeling Epidemic Spreading through Public Transit using Time-Varying Encounter Network
Creator	Tam, Clarence Li, Daqing Shen, Yu Feng, Kairui Mo, Baichuan Yin, Yafeng Zhao, Jinhua
Source	ArXiv
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%22influential passengers%22using the smart card data and isolating them at an early stage can also effectively reduce the epidemic spreading.
has issue date	2020-04-09(xsd:dateTime)
has license	arxiv
sha1sum (hex)	e6c21aa56e844647e941a19470da267b388d0b8d
resource representing a document's title	Modeling Epidemic Spreading through Public Transit using Time-Varying Encounter Network
resource representing a document's body	covid:e6c21aa56e844647e941a19470da267b388d0b8d#body_text
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