This mention in your post is very important :
For instance, there were some periods of time during the study where lots of news about H1N1 were reported, which distorted the results if not handling those periods specially.
One of the most famous examples of this in datascience is when Google tried to predict the flu, but left out some fundamental biases from their analysis, leading to really bad results. You can read more about this here, here and here.
Thank you! Will surely look into the articles!