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ISDS 2016 Conference Abstracts

Wikipedia: a tool to monitor seasonal diseases 
trends?
Pascal Vilain*1, Sophie Larrieu1, Sébastien Cossin3, Céline Caserio-Schönemann2 and 
Laurent Filleul1
1French national public health agency, Regional unit (Cire) Océan Indien, Saint-Denis, Réunion; 2French national public health 
agency, Paris, France; 3French National Institute of Health and Medical Research, Unit 1219, Bordeaux, France

Objective
To explore the interest of Wikipedia as a data source to monitor 

seasonal diseases trends in metropolitan France.

Introduction
Today, Internet, especially Wikipedia, is an important part of 

everyday life. People can notably use this popular free online 
encyclopedia to search health-related information. Recent studies 
showed that Wikipedia data can be used to monitor and to forecast 
influenza-like illnesses in near real time in the United States [1,2].  
We carried out a study to explore whether French Wikipedia data 
allow to monitor the trends of five seasonal diseases in metropolitan 
France: influenza-like illness, gastroenteritis, bronchiolitis, 
chickenpox and asthma.

Methods
To collect Wikipedia data, we used two free web applications 

(https://stats.grok.se and https://tools.wmflabs.org/pageviews), which 
aggregate daily views for each French entry of the encyclopedia.

As some articles have several entries (redirects), we collected 
view statistics for all the article entries and added them to make time 
series from January 1st, 2009 to June 30, 2016 (Figure 1). Then, we 
compared these data to those of OSCOUR® network, which is a robust 
national surveillance system based on the emergency departments. 
For each disease, we modelized daily variations in Wikipedia views 
according to daily visits in ED using Poisson regression models 
allowing for overdispersion. The following adjustment variables were 
included in the model: long-term trend, seasonality, day of the week. 
We tested several lags (day-7 to day+7) in order to explore whether 
one of the two indicators (Wikipedia view or ED visits) varied earlier 
than the other.

Results
The mean number of daily views was 764 [16-8271] for influenza-

like illness, 202 [6-1660] for bronchiolitis, 1228 [59-10030] for 
gastroenteritis, 475 [21-2729] for asthma and 879 [25-4081] for 
chickenpox. Times series analyses showed a positive association 
between page views and ED visits for each seasonal disease (Figure 2).  
For each increase in 100 Wikipedia views, the number of ED visits 
the same day increased by 2.9% (95% CI=[2.5-3.3]) for influenza, 
1.8 (95% CI=[1.4-2.2]) for bronchiolitis, 2.4% (95% CI=[2.2-2.7]) 
for gastroenteritis, 1.4% (95% CI=[1.0-1.7]) for asthma and 2.9%  
(95% CI=[1.7-4.1]) for chickenpox. Globally, the highest relative 
risks were observed for lag-1 (day-1) to lag0.

Conclusions
This study allowed to show that French Wikipedia data can 

be useful to monitor the trends of seasonal diseases. Indeed, they 
were significantly associated with data from a robust surveillance 
system, with a maximum lag of one day. Wikipedia can therefore 
be considered as an interesting complementary data source, notably 
when traditional surveillance systems are not available in real time. 

Further works will be necessary to elaborate forecasting models for 
these seasonal diseases.

Figure1. Daily number of page views and ED visits for seasonal dieases, 
January 1st, 2009 to June 30, 2016

Figure2. Relative risk between Wikipedia page views and ED visits for 
seasonal diseases by several lags

Keywords
wikipedia; surveillance; seasonal dieases

References
[1] McIver DJ, Brownstein JS. Wikipedia usage estimates prevalence 

of influenza-like illness in the United States in near real-time. PLoS 
Comput Biol. 2014;10(4):e1003581.

[2] Hickmann KS, Fairchild G, Priedhorsky R, Generous N, Hyman JM, 
Deshpande A, Del Valle SY. Forecasting the 2013-2014 influenza 
season using Wikipedia. PLoS Comput Biol. 2015;11(5):e1004239.

*Pascal Vilain
E-mail: pascal.vilain@ars.sante.fr

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 9(1):e52, 2017