In this paper, we have described an evaluation of a syndromic surveillance system based on queries submitted to the search engine on a Swedish medical website and regularly used during the pandemic influenza period. From our experience, we can say that there are a number of advantages of using web queries as a source for surveillance during a pandemic:
The system is fully automatic;
The estimates are produced earlier than the traditional sources that it is supposed to mimic;
They do not require people to see a doctor;
There is no reporting delay in the system;
The system is cheap to maintain;
A system based on web queries can easily be adapted to different symptoms or diagnoses.
In addition, the presented analyses demonstrated that the system is reliable, stable and performs well when compared with conventional surveillance systems. When comparing the output from our sentinel model to Google Flu Trends for Sweden, we can conclude that although our models had been trained on a substantially smaller set of data, they were at least equivalent to Google Flu Trends in terms of performance, and in terms of peak estimation even seemed to be more precise.
No current method can, however, give us the true spread and impact of an infectious disease in society. Until such a method is invented, the best we can do is to use multiple sources for surveillance, be it an influenza pandemic or another infectious disease. Syndromic surveillance based on web search behaviour clearly has a role to play as such a source.