>When Madan trained software to hunt for this signature in the cellphone data, a daily check correctly identified flu victims 90 per cent of the time.

I'm very surprised by this - it strikes me that I'd expect it to be hard to tell from such data that it wasn't a stomach upset, tiredness, onset of disease or simply a heavy cold. Indeed 90% sounds like it might be higher than correct identification via an interview with a doctor.

>[...] in Rwanda between 2006 and 2009. He saw a clear reduction in people's movement, which may have been due to the disease. But the outbreak was caused by floods, which also limited mobility. Distinguishing between the two possible causes on the basis of phone data alone was impossible, he says.

Makes me the 90% figure highly suspect.

That aside I wonder if it wouldn't be easier to have a smart phone app that gives you epidemiology info in return for entering your health status for the day. To encourage continued use a sort of diary function and stats could be added. Wouldn't this be more predictive than monitoring movement, and less intrusive?