That was a very different beast. It relied on using Google searches to infer the prevalence of various Influenza Like Illnesses in real time, while the CDC reports data with a 2-week lag. Notably, some of the queries they found to be correlated were... strange... like NBA results.
Not unsurprisingly (in hindsight, at least) [2], this eventually broke down when epidemics and flu symptoms got in the news and completely changed what people were searching for.
> Notably, some of the queries they found to be correlated were... strange... like NBA results.
Doesn't seem that strange to me.
The presence of a professional sports team in your area is correlated with an increase in flu rates. Getting an ice hockey (NHL) is pretty much the worst.
That's definitely one factor, but from what I recall (it's been a while) the connection was slightly more subtle. The NBA season (Oct-Apr) overlaps the flu season (Dec-Feb) so if people are googling NBA results you're in either in or close to the typical flu season. If the NBA decided to change their schedule, the correlation would go away.
Yeah I know its way different methods. Sorry for being disingenuous. The point of my snarking was that google made a lot of noise about Google Flu but then quietly got rid of it when it didn't work. To me Googles research has a tendency to be more about headlines than actually solving problems.
No worries, Google does tend to do a good job of monopolizing attention in whatever they do and Epidemic Modeling is... complicated. Probably much more complicated than pretty much any other kind of modeling since people have the bad habit of thinking and acting in whatever way they want (sometimes with the explicit purpose of breaking your model :).
Now, if you want to see the real-world state-of-the-art epidemic modeling on a global scale, checkout GLEaM/GLEaMViz https://www.gleamviz.org/ (full disclaimer, in a previous life I was the lead developer).
And if you're interested in a basic intro, you can also checkout my (somewhat neglected) series of blog posts from the pandemic days: https://github.com/DataForScience/Epidemiology101 </ShamelessSelfPromotion>
That was a very different beast. It relied on using Google searches to infer the prevalence of various Influenza Like Illnesses in real time, while the CDC reports data with a 2-week lag. Notably, some of the queries they found to be correlated were... strange... like NBA results.
Not unsurprisingly (in hindsight, at least) [2], this eventually broke down when epidemics and flu symptoms got in the news and completely changed what people were searching for.
[1] https://www.nature.com/articles/nature07634
[2] https://www.science.org/doi/10.1126/science.1248506