About: 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.   Goto Sponge  NotDistinct  Permalink

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

AttributesValues
type
value
  • 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.
Subject
  • Influenza
  • Vaccine-preventable diseases
  • Tokyo
  • Network theory
  • Animal viral diseases
  • Healthcare-associated infections
  • RTT
  • RTTEM
  • Computational problems in graph theory
part of
is abstract of
is hasSource of
Faceted Search & Find service v1.13.91 as of Mar 24 2020


Alternative Linked Data Documents: Sponger | ODE     Content Formats:       RDF       ODATA       Microdata      About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data]
OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software