Hulth and Rydevik BMC Public Health 2011, 11:252 http://www.biomedcentral.com/1471-2458/11/252 the system is shown. Each night the search log for the previous day is automatically transferred to SMI from the company hosting the Vårdguiden search engine (Euroling). The query terms are extracted from the log and stored in a database, together with the date of sub- mission to Vårdguiden. In the database, we have data from week 27, 2005. The queries are aggregated by week. This aggregation level can easily be altered if required for tailored analyses. For all analyses described in this paper, the results are assumed to reflect the nation as a whole. The system can be accessed through a designated HTML page on the SMI intranet. On that page, the user can request time series for up to five unique queries for the last five years, counting backwards from the week before the request is made. The matching of a user request to the queries submitted to Vårdguiden is done in a generous fashion. For example, counts on vomit will include both projectile vomiting and vomit and pregnancy (denoted *vomit*, where the star means any prefix or suffix). Also, the matching is done irre- spectively of case. When multiple variants of one query type are to be added, the user can specify this by using a pipe sign, for example state diarre|diarré, to account for two spelling alternatives of diarrhoea in Swedish. If the search patterns are deemed interesting, more sophis- ticated analyses of the data can then be initiated. These tailored analyses are initially carried out outside the GET WELL framework, but if successful, may be incor- porated into the system. The result is presented on a web page in the form of a graph. If an email address is provided, the graph is also sent by email. It is also possible to subscribe to emails that are then automatically dispatched by GET WELL. The email can contain either graphs of time series of particular queries or the output from tailored statistical analyses developed in collaboration with the epidemiolo- gist. The emails are normally sent once a week, as this is the default aggregation level of data. Currently there are two diseases (influenza and norovirus infection) for which tailored statistical analyses are made on a regular basis by GET WELL, and for which automatic emails are sent each week to predefined recipients. It can be assumed that media affect search behaviour, in that more frequently covered subjects will lead to more queries on the subjects in question. For this rea- son the GET WELL users have an option to also have the number of articles in online news media per week on their subject of choice plotted in the generated graph. This number is fetched from a Swedish search engine for news [12]. The web front-end and the e-mail submission compo- nent are implemented in Java. The normalization, the plot generation, and the statistical analyses are Page 3 of 8 implemented in R, while the rest of the components are written in Perl. The query log transfer is realized using Curl. Batch scripts are used to control the flow. A moti- vation behind the choices of technologies was that they are available as open source software at no cost to the user. Also, Perl is suitable for the required string matching. Search volume and normalization In Figure 2, the total number of queries submitted to the search engine per week on Vårdguiden is plotted. In this graph, data from June 2005 to December 2009 are displayed. The broken line in June 2006 is due to five weeks of missing logs. As can be seen in the figure, the total number of queries has increased over time, although not as steeply now as in 2005 and 2006. The large peak in the autumn 2009 was probably due to the influenza A(H1N1) pandemic, as Vårdguiden was one recommended place for information. Because of the increase in search volume over time, we need to nor- malize each query to get a veracious picture of any divergence from the search trend over time for a parti- cular query. The increase in the total number of sub- mitted web queries per week is large over the period, which means that the difference between January and December is also large. We can therefore not use the total number of queries during a whole year for normal- izing. As can be noted in Figure 2, there is also a seaso- nal variation in the total number of submitted queries, with more queries during the Swedish winter season than during the summer season. This means that we Figure 2 Total number of queries to Vårdguiden.se. The total number of queries submitted to the Vårdguiden search engine from June 2005 to December 2009, aggregated by week.