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A comment on The Parable of Google Flu: Traps in Big Data Analysis [pdf]. Parent comment

Re:The Parable of Google Flu: Traps in Big Data Analysis [pdf] by Fomite on Monday March 24, 2014 @11:22AM (#7458711)
The key is, like all population studies, the CDC doesn't have to know about you. It has to know about some people like you, and honestly, if you were well enough to not need to go to the doctor, it's also not really the influenza public health authorities are worried about.

The CDC is unapologetic about their data being estimates - but they're very solid estimates, and match more intensive but smaller scale studies pretty well. But we don't need to capture every single flu case - no surveillance system will ever do that, nor need to.

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Re:The Parable of Google Flu: Traps in Big Data Analysis [pdf] by colin_mccabe on Monday March 24, 2014 @11:07PM (#7463558)
I just feel like either I am missing something, or there is a lack of rigor here. Clearly, sampling introduces errors and under-reporting introduces errors. What I am looking for is a case (based on data, not hand-waving) that Google's errors are worse than the CDC's, and so far I'm just not seeing it. Maybe I am missing something which is obvious to people in the field.

Edit: I see how the CDC's numbers could be a lower bound, but not upper.

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