About: Detecting the outbreak of influenza based on the shortest path of dynamic city network

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Detecting the outbreak of influenza based on the shortest path of dynamic city network
Creator	Liu, Rui Yang, Kun Chen, Pei Chen, Yingqi Liu, Zhengrong Xie, Jialiu Xie, Rong
Source	PMC
abstract	The influenza pandemic causes a large number of hospitalizations and even deaths. There is an urgent need for an efficient and effective method for detecting the outbreak of influenza so that timely, appropriate interventions can be made to prevent or at least prepare for catastrophic epidemics. In this study, we proposed a computational method, the shortest-path-based dynamical network marker (SP-DNM), to detect the pre-outbreak state of influenza epidemics by monitoring the dynamical change of the shortest path in a city network. Specifically, by mapping the real-time information to a properly constructed city network, our method detects the early-warning signal prior to the influenza outbreak in both Tokyo and Hokkaido for consecutive 9 years, which demonstrate the effectiveness and robustness of the proposed method.
has issue date	2020-07-20(xsd:dateTime)
bibo:doi	10.7717/peerj.9432
has license	cc-by
sha1sum (hex)	75465bd52677b747c59395668fe46b750cc04560
schema:url	https://doi.org/10.7717/peerj.9432
resource representing a document's title	Detecting the outbreak of influenza based on the shortest path of dynamic city network
has PubMed Central identifier	PMC7377247
schema:publication	PeerJ
resource representing a document's body	covid:75465bd52677b747c59395668fe46b750cc04560#body_text
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