The autoregressive model uses the last two reported flu levels. It essentially predicts that this week’s flu level is the same as last week’s level adjusted by either an upward or downward trend as inferred from the earlier week.

However, in my experience, sometimes you have to watch out with AR models, because sometimes they just say that the best least squares estimator (given an AR model) is to forecast that the next value is basically the same as the last. The error of such a model can be very good in numerical terms, but as a forecast it might not be so good, because it can “miss” (i.e. the forecast lags) every turning point in the time series. So, the forecast curve can look like the actuals shifted to the right by some time period. It’s hard to tell if that’s what is happening in the figure.

It seems to me that a hybrid system could be useful in a lot of health contexts — use the search engine results to suggest online polling that could be done on a more scientific basis. [and, yes, I did use "online polling" and "scientific" in the same sentence -- I'm amazed as well].