A more realistic model
Juanes' studies of the flow of fluids through fracture networks in subsurface rock and the research of CEE's Marta Gonzlez, who uses cellphone data to model human mobility patterns and trace contagion processes in social networks, laid the basis for determining individual travel patterns among airports in the new study. Existing models typically assume a random, homogenous diffusion of travelers from one airport to the next.
However, people don't travel randomly; they tend to create patterns that can be replicated. Using Gonzlez's work on human mobility patterns, Juanes and his research group including graduate student Christos Nicolaides and research associate Luis Cueto-Felgueroso applied Monte Carlo simulations to determine the likelihood of any single traveler flying from one airport to another.
"The results from our model are very different from those of a conventional model that relies on the random diffusion of travelers [and] similar to the advective flow of fluids," says Nicolaides, first author of a paper by the four MIT researchers that was published in the journal PLoS ONE. "The advective transport process relies on distinctive properties of the substance that's moving, as opposed to diffusion, which assumes a random flow. If you include diffusion only in the model, the biggest airport hubs in terms of traffic would be the most influential spreaders of disease. But that's not accurate."
Outsize role for Honolulu
For example, a simplified model using random diffusion might say that half the travelers at the Honolulu airport will go to San Francisco and half to Anchorage, Alaska, taking the disease and spreading it to travelers at those airports, who would randomly travel and continue the co
|Contact: Denise Brehm|
Massachusetts Institute of Technology