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Influenza01:27

Influenza

Influenza is an acute, highly communicable viral disease that affects the respiratory tract and is responsible for seasonal epidemics worldwide. Influenza A is the most prevalent type associated with widespread outbreaks and is subtyped based on two surface glycoproteins: hemagglutinin (H) and neuraminidase (N), as in H1N1. These glycoproteins are essential for viral infectivity, transmission, and immune recognition. Transmission occurs primarily through respiratory droplets and contaminated...
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Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
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Investigation of Disease Outbreaks

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High-throughput Detection Method for Influenza Virus
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High-throughput Detection Method for Influenza Virus

Published on: February 4, 2012

Grid-based International Network for Flu observation (g-INFO).

Trung-Tung Doan1, Aurélien Bernard, Ana Lucia Da-Costa

  • 1Institut de la Francophonie pour l'Informatique, L'équipe Modélisation et Simulation Informatique, 42, Ta Quang Buu, Hanoi, Vietnam.

Studies in Health Technology and Informatics
|June 15, 2010
PubMed
Summary

A global surveillance network using grid technology was developed to track H1N1 influenza evolution. This system automates molecular epidemiology studies for enhanced pandemic monitoring.

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Area of Science:

  • Public Health
  • Infectious Disease Epidemiology
  • Bioinformatics

Background:

  • The 2009 H1N1 pandemic highlighted the need for robust public health surveillance.
  • Molecular epidemiology is crucial for understanding viral evolution and spread.
  • Existing surveillance systems require enhanced capabilities for emerging threats.

Purpose of the Study:

  • To propose and prototype a global surveillance network for influenza using grid technology.
  • To automate molecular epidemiology studies for timely analysis of viral data.
  • To provide a platform for real-time monitoring of influenza pandemics.

Main Methods:

  • Development of a global surveillance network leveraging grid technology.
  • Federation of influenza data servers and automated deployment of molecular epidemiology studies.
  • Utilizing AMGA and WISDOM Production Environment for data extraction from NCBI.
  • Phylogenetic analysis pipeline deployed on EGEE and AuverGrid e-infrastructures.

Main Results:

  • A functional prototype of the global surveillance network was successfully deployed.
  • Daily extraction and processing of H1N1 influenza sequence data from NCBI.
  • Automated phylogenetic analysis of viral strains.
  • Results visualized on a web portal for epidemiologists.

Conclusions:

  • Grid technology offers a viable solution for federating global health data.
  • Automated molecular epidemiology studies enhance pandemic surveillance capabilities.
  • The developed network provides a valuable tool for monitoring H1N1 pandemics and future threats.