tetano
Editor, Senior Moderator
PLoS One. 2013 May 17;8(5):e64156. doi: 10.1371/journal.pone.0064156. Print 2013.
Eight years of the great influenza survey to monitor influenza-like illness in flanders.
Vandendijck Y, Faes C, Hens N.
Source
Interuniversity Institute for Biostatistics and statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium.
Abstract
In 2003, an internet-based monitoring system of influenza-like illness (ILI), the Great Influenza Survey (GIS), was initiated in Belgium. For the Flemish part of Belgium, we investigate the representativeness of the GIS population and assess the validity of the survey in terms of ILI incidence during eight influenza seasons (from 2003 through 2011). The validity is investigated by comparing estimated ILI incidences from the GIS with recorded incidences from two other monitoring systems, (i) the Belgian Sentinel Network and (ii) the Google Flu Trends, and by performing a risk factor analysis to investigate whether the risks on acquiring ILI in the GIS population are comparable with results in the literature. A random walk model of first order is used to estimate ILI incidence trends based on the GIS. Good to excellent correspondence is observed between the estimated ILI trends in the GIS and the recorded trends in the Sentinel Network and the Google Flu Trends. The results of the risk factor analysis are in line with the literature. In conclusion, the GIS is a useful additional surveillance network for ILI monitoring in Flanders. The advantages are the speed at which information is available and the fact that data is gathered directly in the community at an individual level.
PMID:
23691162
[PubMed - in process]
PMCID:
PMC3656949
Free full text
http://www.ncbi.nlm.nih.gov/pubmed/23691162
Eight years of the great influenza survey to monitor influenza-like illness in flanders.
Vandendijck Y, Faes C, Hens N.
Source
Interuniversity Institute for Biostatistics and statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium.
Abstract
In 2003, an internet-based monitoring system of influenza-like illness (ILI), the Great Influenza Survey (GIS), was initiated in Belgium. For the Flemish part of Belgium, we investigate the representativeness of the GIS population and assess the validity of the survey in terms of ILI incidence during eight influenza seasons (from 2003 through 2011). The validity is investigated by comparing estimated ILI incidences from the GIS with recorded incidences from two other monitoring systems, (i) the Belgian Sentinel Network and (ii) the Google Flu Trends, and by performing a risk factor analysis to investigate whether the risks on acquiring ILI in the GIS population are comparable with results in the literature. A random walk model of first order is used to estimate ILI incidence trends based on the GIS. Good to excellent correspondence is observed between the estimated ILI trends in the GIS and the recorded trends in the Sentinel Network and the Google Flu Trends. The results of the risk factor analysis are in line with the literature. In conclusion, the GIS is a useful additional surveillance network for ILI monitoring in Flanders. The advantages are the speed at which information is available and the fact that data is gathered directly in the community at an individual level.
PMID:
23691162
[PubMed - in process]
PMCID:
PMC3656949
Free full text
http://www.ncbi.nlm.nih.gov/pubmed/23691162