Hulth and Rydevik BMC Public Health 2011, 11:252 http://www.biomedcentral.com/1471-2458/11/252 disease since the beginning of the A(H1N1) pandemic in April 2009 affected the usage of the two sites. It also enabled us to compare the two search engines’ search patterns with the traditional influenza surveillance for Sweden. For the Google data, we entered the term influ- ensa selecting data for the “last twelve months” (week 50, 2008 to week 49, 2009). For the Vårdguiden data, we counted all queries where *influensa* occurred for the same time period. Five curves are shown in Figure 5. The two upper curves show data from Google Insights for Search and Vårdguiden on the query influensa. To show the benefit of tailored analyses compared to just plotting the time series of a particular query, we have in the graph included the output of Google flu trends for Sweden [3] as well as the output of a tailored influenza model we developed [7], for the same time period. The third curve from the top shows the output from Google flu trends, while the fourth curve shows the output from our tai- lored influenza surveillance. Both these statistical models were developed on sentinel influenza data from Sweden, and combine a number of different queries related to influenza. In the figure, the “gold standard” of the senti- nel reports is also displayed as a reference, showing the proportion of patients with influenza-like illness visiting Figure 5 Data on “influenza”, 2009. From the top: queries on influenza on Google according to Google Insights for Search (data are normalized and scaled); queries on influenza on the medical web site Vårdguiden (data are normalized); Google flu trends estimates; estimates from tailored Vårdguiden model; sentinel influenza data reported to SMI. Data are from week 50, 2008 to week 49, 2009. Page 5 of 8 any of the sentinel general practitioners in Sweden for the same period (the bottom curve). During the investigated period, influenza received a lot of attention. When visually comparing the results from the two search engines on the query influensa in Figure 5, the search patterns are quite similar. The two most pronounced differences are the large peak in May found in the Google data, and the relatively small peak in Feb- ruary for the Vårdguiden data, during the seasonal influ- enza peak. The Google peak in May reflects the classification of the A(H1N1) epidemic as a pandemic by WHO. The large number of queries on influenza during the A(H1N1) pandemic peak (in November, 2009) hides the height of the seasonal peak in February in the Vårdguiden curve. When visually comparing the output from the two more complex statistical models that incorporate different queries, we can see that Goo- gle flu trends have a higher first peak compared to the second peak, while the second peak is higher for the Vårdguiden model. The height of the peaks estimated by the Vårdguiden model is consistent with the sentinel reference data. It is interesting to note that for Google data, the query on influenza alone seems to be a better estimate for the influenza spread in Sweden, with the exception of the huge media attention in April 2009. In summary, the best estimates are produced by the tai- lored influenza model based on Vårdguiden queries. It is also interesting to note that all four curves based on web queries peak one week before the traditional surveillance. Vomit The term vomit was selected because it is more often part of a compound in Swedish, and might therefore illustrate a potential problem when the user cannot fully control the extraction process. For the Google data, we entered the term kräkningar (kräkningar is the most common word for the stem kräk in the Vårdguiden database). For the Vårdguiden data, we counted all queries where kräkningar and *kräk*, respectively, occurred. For the vomit analysis we used search queries from week 27, 2005 to week 4, 2010. In figure 6, the search pattern for the query kräknin- gar (vomit) obtained from Google Insights for Search is shown, together with two curves from Vårdguiden showing kräkningar and *kräk*. In this figure, data from slightly more than three years on the query are dis- played (week 1, 2007 to week 4, 2010). We excluded early data (from week 27, 2005) as the Google data con- tained a large number of zeros for that period. In the Vårdguiden data on kräkningar, there is a clearer sea- sonality compared to the Google data, retrieved on exactly the same query. As previously mentioned, Swed- ish is rich in compounding and to illustrate how this affects visitors’ query formulation, we also plotted the