The search engine does not log any information on the users submitting the queries, not even the IP-address which theoretically could pin-point the user geographically. The data are therefore aggregated on a national level, meaning that only national outbreaks and trends can be discovered. In February 2008, Vardguiden performed a survey directed to the visitors of the web site. In total 1,224 persons were questioned, out of which 1,000 replied. According to this survey, 85.1 per cent of the visitors were women. The majority of all visitors were between 21 and 35 years old, and 63.4 per cent lived in the Stockholm County. Of the respondents, 74.3 per cent used the search engine on the web site to look for the information they require.
As timeliness may be crucial in the case of an outbreak, sources conveying as early outbreak indicators as possible should be identified. Zeng & Wagner have constructed a model : based on health psychology literature : on people's behaviour when falling ill. The model consists of four phases: recognition of symptoms, interpretation of symptoms, cognitive representation of illness, and seeking treatment. The model implies that outbreak indicators are found in different sources depending on which phase the infected persons are in. For the first phase, one potential source are records of absenteeism. During the second and third phases, the social surrounding plays an important role. Also, ill people may seek advice on medical help lines and web sites during these two phases. The model shows the natural delay between noting of symptoms and seeking treatment by, for example, visiting a pharmacy or a health centre, which is done only during the fourth phase. According to Zeng & Wagner the queries will reflect a person's symptoms when in the second phase (interpretation of symptoms), while during the third phase (cognitive representation of illness) the search terms are more disease oriented. Consequently, the queries reflecting symptoms should be an even earlier indicator than queries reflecting diagnosis. In theory, this model probably has great bearing, but the acuteness of an influenza illness means that it is difficult to discern the phases with the time resolution used in this study. However, if the queries could be analysed momentaneously, such an approach would probably allow for a more accurate representation of the epidemic pattern.
Andersson et al. have shown that the sentinel reports cannot be used to predict the number of laboratory verified cases in the Swedish data set. This fact is a strong argument for complementing the influenza surveillance with analyses based on other data sources. By : as in this study : using web query data, it is also possible to obtain a baseline for the time of the year when no conventional influenza surveillance is performed. In addition, public holidays such as Christmas, when seeing a GP is more difficult, are covered with this source. Assumingly, different strata of the population are covered by the web queries, compared to those covered by the reporting from the health care. The use of the internet is increasing, and we can therefore expect to get more and more data points, and consequently more reliable results. With time, the internet will be an integrated part of most citizens' life and for this reason we will also get a much more diverse group of users. Thus, the web queries have the potential to reflect the population as a whole. This is opposed to the sentinel system as well as the laboratory testing, which probably over-report groups that are more vulnerable to the disease.
With the presented study we show that web queries can indeed be a reliable and cost-effective source for identification and estimation of the development of the aggregated influenza activity in a society. We feel that this first, scientific evaluation of its usefulness is an important proof of concept that could stimulate further investigations, and also an important foundation for reliable exploitation of similar systems for various kinds of surveillance. Web query logs are obtained at a low cost, and give a unique access to ill individuals who may yet not be seeking care. This paper shows the potential of web queries as an accurate and labour extensive source for syndromic surveillance. In future work, we will explore how to best utilize the web queries for other diseases, with characteristics different from influenza, such as norovirus infections.