2. Sore throat? Sniffles?Sore throat? Sniffles?  Google it! Duh!  During flu season, more people enter search queries concerning the flu.  Each year 90 million American adults search web for info about specific illnesses = LOTS OF DATA  Importance: 250,000 - 500,000 deaths from respiratory illnesses worldwide.

3. Previous AttemptsPrevious Attempts  Swedish website counted queries in order track flu activity.  There was a strong correlation between frequency of search terms containing “flu” and “influenza” and virologic surveillance data  These models look for a very limited number of queries.

4. Google’s VersionGoogle’s Version  Took 50 million of the most common search queries between 2003-2008 and did a weekly count for each state  Normalized data by dividing count by total searches for the week (thereby getting a percentage)

5.  Each of 50 million queries were tested for correlation with CDC data  Ranked according from most to least correlated  We want to estimate flu activity based on more then just a few queries

6.  Google added top ranked queries together to see what number would yield the most accurate results.  The magic number is 45

7.  Previously unused data for flu season of 2007-2008 as a test set  The mean correlation was 0.97 (ranged between 0.92 and 0.99)

8. Advantages  Generate accurate estimates faster than CDC.  CDC takes one to two weeks to process data and generate a flu activity report  It takes Google one to two days to generate an estimate  Faster estimates means that health officials can quickly direct resources to where the need is greatest

9. Future  Expand Google Flu Trends to predict flu activity across the globe.  Challenges: some countries do not have official historical data