‘Run, Don’t Fight’: How to Survive a Zombie Apocalypse — with Math

A Summer Science Scholar studied complicated mathematical models to develop evasion strategies for survivors of a zombie apocalypse in Gambier.

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Anyone worried about surviving a zombie apocalypse this Halloween might want to become good friends with Quang Doan ’28. 

That’s because the double major in math and physics spent his summer working on a complex mathematical model to determine the best path of escape for anyone who comes face to face with hordes of the undead.

His project calculating optimal evasion strategies — called “Run, Don’t Fight: A Zombie Apocalypse Model” — was undertaken as a Kenyon Summer Science Scholar under the mentorship of Assistant Professor of Mathematics Marissa Gee.

And while Doan’s model should get the job done for anyone who finds themself trapped in a Kenyon residence hall while zombies roam around Middle Path, it also has plenty of other real-world applications. 

It’s the same sort of math, Gee said, that she might use to plot the safest route for a rover crossing difficult terrain on Mars or to understand movements between predators and prey in the wild.

“Part of what I want any student to take away from something like this is the power of mathematical modeling and a sense of how we can go from a real-world problem to a mathematical equation to represent that problem,” she said. “I want students to work on whatever’s going to get them excited. If that’s zombies, then let’s work on zombies.”

Doan has a longstanding interest in the undead, having enjoyed watching them in movies, television series and video games like “Project Zomboid.”  

“Actually, I know a little too much about zombies,” he said.

This project offered a perfect opportunity for him to put this knowledge to use in a mathematical context. But first, he needed to make some important decisions: Are the zombies that take over campus slow and stupid — think “Night of the Living Dead” — or frighteningly fast, like “28 Days Later”? Doan decided on the former, allowing their movements to be governed by random diffusion.

Other variables needed to be considered as well, including terrain and the slope of the landscape. Forests offer more places to hide; open spaces increase the chances of being spotted.

“We used real open-source data online to try to model the terrains and speed of the humans,” Doan said. “Once we have that, we merge everything together and use (classic) equations and try to solve the path that a human should take.”

For the purposes of his project, Doan assumed that a single survivor was in the North Campus Apartments and had two hours to make it across campus, through 2,000 infected zombies, to a rescue zone by the Kokosing River. But thanks to a web app that Doan created, he can change any of those variables and the math will plot an optimal escape path. 

“We like the Gambier example because it’s very evocative,” Gee said. “But the math itself is extremely flexible. We can change the location, the deadline, the location of zombies, the number of zombies. All of that stuff is something that you can customize to whatever scenario you’re interested in.”

Doan has presented his work multiple times on campus and will give a talk as part of an undergraduate research session at the Joint Mathematics Meetings hosted by the American Mathematical Society this January in Chicago.

In the meantime, he’s happy to keep talking to anyone who will listen.

“This has been my passion project since high school,” said Doan, who recalls watching a YouTube video tracking a theoretical zombie outbreak when he was a student growing up in Vietnam. “It’s cool to actually do a math project on zombies. I got to learn about numerical methods and actually use my knowledge from classes and courses and merge everything into a large project.”

And he has a little advice for anyone who may find themselves in this sort of harrowing situation — just in case.

“You really don’t want to fight zombies,” he said. “Just run away from them.”

And make sure you have his app with you when you do.