The fire is blazing. It burns everything in its path. Houses, animals, people; nothing stops it.
So where do you send the firefighters? Where will the flame strike next?
Doctors Loren Cobb and Jan Mandel, professors in the Department of Mathematical and Statistical Sciences at UC Denver, are asking the same question about epidemics, albeit in a different manner.
Where do you send the doctors? Where will H1N1 strike next?
In order to answer these questions, Cobb and colleagues are working on a mathematical model that would predict the path and danger of the disease in real time.
“Just in the last year and a half that I’ve been at UC Denver, I became aware of some really sophisticated systems that were available to track wildfires,” said Cobb. “The math of wildfires [is] almost identical to the math of epidemics.”
Lynn Bennethum, associate chair of the math department, had also worked with the wildfire tracking model. “Models are an approximation,” she said. “If you throw a ball, you can use Newton’s Second Law of motion to get an approximation of where it will land. However, in real life, there are things like wind and temperature conditions that will have effects on it.”
“The purpose of models is not just to predict,” Bennethum said, “but to see what effects change the spread of disease.”
The model Cobb and Mandel are trying to create works in two main ways. Using mathematic algorithms and equations that soar above many peoples’ heads, the model would predict where a certain epidemic will move next, how hard it will strike, etc.
But the math is only one part of it. While the equations are busy chugging away, real-time data will be collected. Researchers hope that this real-time data, slapped together with a strong mathematical backbone, could help world health organizations as well as local physicians prepare for the oncoming onslaughts of an epidemic.
And this isn’t Cobb’s first time at the simulation rodeo.
“I’ve done simulations of epidemics before, over the past six years ago or so,” said Cobb. “It seemed to me the techniques that I’d recently learned about meteorology might do a whole lot better at tracking epidemics.”
Even with the experience and the manpower, the model still needs work.
“So far, we’ve implemented a very nice simulation that adheres closely to mathematic principles,” said Cobb. “It could be improved upon, perhaps quite a lot.”
And even with the model performing to the best of its ability, it still might not be perfect.
“It’s like the weather,” Bennethum said. “You’re never gonna get it exactly right.”
Knowing where and how hard a certain disease will strike, even if it’s just an estimate, could be invaluable to health professionals.
“The National Library of Medicine is really serious about the problem of tracking emerging diseases,” Cobb explained. And this need is what gave the team a $710,000 grant on Oct. 1 in order to work on this program.
So what drives Cobb to work on this model, slaving away hours over a hot computer?
“Personally, I think that this general new category of methods is going to have a revolutionary impact on all of the social sciences, and I count epidemiology as a social science,” Cobb said. “This project could be the first in a series in which we will push methodology into the social sciences. We could create dynamic moving maps of phenomenon.”
Jargon aside, that basically means researchers could track any sort of social trend. This means anything from disease to unemployment to illiteracy could be tracked and predicted.
The team is confident. When Cobb was asked if he believed their results would be enough to have their funding expanded, he said, “Oh yes.”
“I’m hopeful,” said Cobb. “We need some serious mathematics to make it happen, but I’m hopeful.”
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