Google Disease Trends: Can search query trends provide the basis for an accurate, reliable model of real-world phenomena?

Can search query trends provide the basis for an accurate, reliable model of real-world phenomena?

I was listening to an interesting radio interview today, about a new venture of the Google empire; namely Google disease trends. The purpose of these maps is to estimate disease outbreaks. We have all surely experienced the agony of being ill and using the Internet to search for symptoms or treatment of whatever condition we may have. Those kind of searches is exactly what Google uses to estimate diseases, with the presumption that Each week, millions of users around the world search for health information online. As you might expect, there are more flu-related searches during flu season, more allergy-related searches during allergy season, and more sunburn-related searches during the summer.(http://www.google.org/flutrends/) 

Those search terms is what Google uses as indicators of flu activity. Google Flu ( that is the name of the service) thus uses aggregated Google search data to estimate current flu activity around the world. Google poses the relevant question: Can search query trends provide the basis for an accurate, reliable model of real-world phenomena? 

To answer that question, Google has pulled data from the Ministry of Health in several countries about their past flu activity and their conclusion is that the Google search queries are very closely matched ( see graph by clicking the above link). So why is there a need for estimates from aggregated search data? Google remarks that while many health agencies do have an active flu surveillance programme, they are often focused on one region or country and only updated once a week. Google Flu collates data from several countries and is updated on a daily basis.

From an epidemiologist perspective, early detection is always key when controlling a disease. Early detection of a disease means reduction of the number of people infected or affected. Thus Google states that: Our up-to-date influenza estimates may enable public health officials and health professionals to better respond to seasonal epidemics and pandemics.

Currently Google has established Google Flu Trend and Google Dengue Trend, and currently do not have prospects of including other diseases. 

Here's an explanation from Google about how the data was derived:

We have found a close relationship between how many people search for flu-related topics and how many people actually have flu symptoms. Of course, not every person who searches for "flu" is actually sick, but a pattern emerges when all the flu-related search queries are added together. We compared our query counts with traditional flu surveillance systems and found that many search queries tend to be popular exactly when flu season is happening. By counting how often we see these search queries, we can estimate how much flu is circulating in different countries and regions around the world. For more information, click the following link - Google published their results in the journal Nature: http://static.googleusercontent.com/external_content/untrusted_dlcp/research.google.com/en//archive/papers/detecting-influenza-epidemics.pdf

Flu trends in "the real world" 

Health agencies use different methods to measure flu activity in a population. Google terms those as traditional collection mechanisms.  Influenza-like illness (ILI), acute respiratory infection (ARI), and virological data are different means of measuring. ILI is often tracked by  the percentage of doctor visits each week, thus gathering data from sentinel healthcare providers. In case of a high ILI percentage, a large fraction of the patients are experiencing flu-like symptoms, and may indicate a public health inquiry to identify the pathogen(s) involved. ARI is, similar to ILI, measured by gathering data from sentinel healthcare providers by tracking the percentage of doctor visits each week. However, influenza is one cause of ARI. Virological data measures laboratory confirmed cases of influenza. A total number of samples tested under the positive laboratory confirmed cases will provide a percentage of the total % of confirmed cases of influenza. 

Surveillance systems often rely on both virological and clinical data. As explained by Google: A network of sentinel laboratories may perform virologic testing by counting and classifying influenza viruses collected from patients, while a network of sentinel physicians will report the fraction of patients presenting with an influenza-like illness (ILI) or acute respiratory infection (ARI).

I wonder what ( if any) meaning it could have that this kind of information is easily accessible ( rather than being in specific reports on specific webpages and may be hard to track down yet even comprehend). Could it have the reverse effect and rather than detecting disease early, people will form their disease patterns depending on the data shown in these maps? I am sure several people( myself included) are familiar with looking up certain symptoms and believing that the symptoms surely must be cancer or another serious disease. The Internet can thus be both a blessing but also somewhat a curse in terms of disease prevention or detection. Exactly because it is updated on a weekly basis, could it assist more "paranoia" in people in "the real world"? And since it provides people with global data would it mean that more people may be investing in flu shots if a neighbouring country has a rise in cases of influenza?