The modeled ebb and flow, uncannily synced to Blue Danube's waltz and simulated to predict flu virus transmission rates, is remarkably swarm-like in its sheer randomness.
Big, bad, vertiginous cities like New York are for sheeple, man. Residents, no matter what they tell you, all follow predictably boring routines and routes in accordance with the laws of work, school, pleasure, or all three. Compare that to someplace in the developing world--Iquitos, Peru, say--and immediately you'll see the daily movements of residents following far more random patterns.
It's this scattershot tendency that makes something like The Dance of City Life, a new data visualization by Emory University post-doc Donal Bisanzio, so mesmerizing. Researchers used GPS technology to quantify "the movement and contact dynamics" of some 600 Iquitos locals over the span of a few days. The modeled ebb and flow, uncannily synced to Blue Danube's waltz and simulated to predict flu virus transmission rates, is remarkably swarm-like in its sheer randomness.
The findings not only suggest that on average Iquitos residents stopped by six locations each day, movements "much more fluid and dynamic" than first-world chumps chasing the Dream. It turns out this could have some pretty huge implications for controlling the spread of infectious disease: "Data on urban mobility," Emory's write up explains, "is critical to responding to infectious disease threats, developing better infrastructure and fostering economic development."