The most risky airports for the spread of disease

The 'house journal' of the Massachusetts Institute of Technology, MIT News, has published a very interesting study on which US airports would be the principal nodes from which an outbreak of infectious disease would spread via travelers.  Here are a few excerpts from their report.

... a new study by researchers in MIT's Department of Civil and Environmental Engineering (CEE) shifts the focus to the first few days of an epidemic, determining how likely the 40 largest U.S. airports are to influence the spread of a contagious disease originating in their home cities. This new approach could help determine appropriate measures for containing infection in specific geographic areas and aid public health officials in making decisions about the distribution of vaccinations or treatments in the earliest days of contagion.

Unlike existing models, the new MIT model incorporates variations in travel patterns among individuals, the geographic locations of airports, the disparity in interactions among airports, and waiting times at individual airports to create a tool that could be used to predict where and how fast a disease might spread.

. . .

Juanes' studies of the flow of fluids through fracture networks in subsurface rock and the research of CEE's Marta González, 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 González'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.

. . .

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 contagion.

In fact, while the Honolulu airport gets only 30 percent as much air traffic as New York's Kennedy International Airport, the new model predicts that it is nearly as influential in terms of contagion, because of where it fits in the air transportation network: Its location in the Pacific Ocean and its many connections to distant, large and well-connected hubs gives it a ranking of third in terms of contagion-spreading influence.

Kennedy Airport is ranked first by the model, followed by airports in Los Angeles, Honolulu, San Francisco, Newark, Chicago (O'Hare) and Washington (Dulles). Atlanta's Hartsfield-Jackson International Airport, which is first in number of flights, ranks eighth in contagion influence. Boston's Logan International Airport ranks 15th.

There's more at the link.  Very interesting and highly recommended reading.

Here's a video animation showing traffic into and out of US airports, based on MIT's new model.  It's immediately obvious which are the major threats for contagion.

It looks like a fascinating study!  It's very interesting what you can do when you combine all sorts of different datasets and run them through a common filter.

Peter