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This Simulator Shows The Relative Chance of Ebola Arriving At The World’s Airports

Even if an infected person steps on a plane, the likelihood that Ebola reaches the U.S. is still very low–and lower still in certain places. Wyoming is looking good.

This Simulator Shows The Relative Chance of Ebola Arriving At The World’s Airports
[Photo: Shutterstock user FedeCandoni]

According to network scientist Dirk Brockmann, one of the best places to avoid an Ebola pandemic is in the high plains of Wyoming. He would know. He just built an interactive simulator showing how and when the virus might arrive at more than a thousand airports around the world.

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In contrast to some of the hysteria surrounding the possibility of the devastating Ebola virus arriving in the United States, Brockmann’s simulator shows that the relative likelihood of an Ebola-infected person from Guinea stepping off a plane, at say, JFK, is a fraction of a percent. And that’s not even measuring the probability that an asymptomatic, Ebola-infected person would step onto a plane in the first place. (It’s almost impossible to quantify that chance–though it could be several thousand times more improbable, Brockmann says.) Instead, the Ebola model begins with the assumption that an infected person steps onto a plane. Then it asks: What happens next?

“It’s human, but there’s a lot of irrationality about this. That’s precisely why I’m so into making these models,” Brockmann says. “People get afraid. The only way you can get rid of this is actual computing these types of numbers that we can better relate to.”


For the last several years, Brockmann has been advancing the concept of effective distance–a way of reorganizing time and space on a map that more accurately reflects how humans move. By tracking human migration in flight patterns, for example, Brockmann and sociologist Dirk Helbing were able to test their theory on the 2003 SARS outbreak and the spread of H1N1 in 2009. The model they developed was able to closely and retroactively predict the arrival times of the viruses on different shores.

Brockmann’s Ebola model, which also tracks the relative probability of an Ebola-infected passenger traveling from Lagos, Nigeria, or Freetown, Sierra Leone, allows anyone to toggle around with “knockout” scenarios–the ability to cut connections between certain airports. But cutting the direct connection between Conakry, Guinea, and Charles de Gaulle airport, for example, has other consequences–and pathways for Ebola to reach Charles de Gaulle still exist. In theory, the model would allow international health authorities to grasp the ripple effects of halting air traffic, looking at tamping down on the global spread of disease as something like a giant game of chess.

The model also turns up unanticipated connections. Airports predicted to be major links in the spread of Ebola reveal the old imprint of European colonialism in Africa. Risk of transmission from former French and British colonies moves more quickly to French and British airports. The Brussels airport also shows up as a major transmission hub.

Brockmann’s now working with German health officials to apply the disease transmission model to real-world scenarios. But there’s a lot that the Ebola model doesn’t take into account, like how people react to the spread of disease on the ground. If you know Ebola risks spreading to your neighborhood, in which direction do you run?

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“That’s still a very unresolved issue,” Brockmann says.

About the author

Sydney Brownstone is a Seattle-based former staff writer at Co.Exist. She lives in a Brooklyn apartment with windows that don’t quite open, and covers environment, health, and data.

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