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Cellphones Handhelds Medicine Stats

Mobile Phone Data Can Track the Spread of Infectious Diseases 21

jan_jes writes: Researchers have used anonymous mobile phone records for more than 15 million people to track the spread of rubella disease in Kenya and were able to quantitatively show that mobile phone data can predict seasonal disease patterns. The researchers compared the cellphone analysis with a highly detailed dataset on rubella incidence in Kenya. They matched; the cellphone movement patterns lined up with the rubella incidence figures. In both of their analyses, rubella spiked three times a year. This showed the researchers that cellphone movement can be a predictor of infectious-disease spread.
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Mobile Phone Data Can Track the Spread of Infectious Diseases

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  • by Anonymous Coward

    No matter what requirements we try using to distinguish successful theories vs wild speculations, apparently people will come up with some sleazy way around them to sound important. If they pre-dicted something, that means that they published a paper earlier claiming a certain relationship between cell phone use and infectious disease. Did this happen?

    • by Anonymous Coward

      Epidemiological mechanisms driving this within year triple peak in incidence are the occurrence of three yearly troughs in transmission

      This data is quite interesting. I had never heard of three peaks in incidence per year. Apparently that is what this data shows, although the above statement is a tautology. They estimated transmission rates from the incidence data, so it makes no sense to say that seasonal changes in transmission rates cause the incidence data... I do wonder if this is due to people being m

      • by Anonymous Coward

        Thinking about this more, I can replace every reference to "seasonal changes in rubella transmission rates" to "seasonal changes in rubella reporting rates". Even in their SIR model, hold transmission rates constant and vary the reporting rates and you can get the exact same output. The exact same paper could be published with totally different conclusion just by switching two terms around a few times. It is not possible to distinguish between the two explanations from this data.

  • FTFY. At least that is what I thought it read when I first glanced at the headline.
    • Infectious diseases on public phones wiped out the Golgafrincians in Hitchiker's Guide to the Galaxy.

      We also know that diseases mutate and evolve.

      Apparently, public phone diseases have evolved from public phones to cell phones, and also from a fictional story to the real world.
  • It's for the kids! They're tracking my mobile phone data so my kids don't get Ebola. Thank you, NSA. What would we do without you?

  • Never take your cell phone when buying weed. That's what I heard.
  • Cell phone movement patterns coincided with annual peaks of German measles (actually renamed Liberty measles during World War I anti-German frenzy in USA) in Kenya. Not sure what else would correlate with annual events. Rains, migratory animals, pollen, food prices, seasonal foods all have some annual rhythm. So there is going to be high correlation between all annual events. So I really don't get what this cell phone movement correlation withe G measles really means.

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