[Image credit: Geoff Oliver Bugbee]
Dirk Brockmann is a leading physicist with the Max Planck Institute in Germany. He is working with colleagues to perfect a model to predict how money moves through space and time. Brockmann will discuss this work and its relevance in predicting the spread of infections diseases at today's session.
The session is taking place at the Muhammad Ali Center in Louisville.
Ethan Zuckerman is sitting next to me and you will get a really nice summary at My Heart's in Accra, I'm sure.
The organization he works for has been renamed to research into "dynamics and self organization," which he jokes lightly about. The old focus was on fluid dynamics, its traditional domain. He's now works on inter-disciplinary methods to tackle tough problems.
Money circulation science is a method for getting at the issue of how infectious diseases travels. It's also revealing about how humans travel.
Showing a picture, he demonstrates how he applies statistics to describe all traffic networks, which are essential models for predicting the spread of disease.
What do we understand about the spacial dynamics of disease, he asks. The Black Death of the 14th century killed about a quarter of the people of Europe, beginning in the southern part of the continent and going north at a few kilometers a days. It also spread in a wave pattern, which can be connected which can be mapped in physics, which means that mathematics can be applied to make predictions.
The dynamic go through three phases, which can be described as SIR - Susceptible, Infected, Recovered. It's been a successful model, but it doesn't work globally. By adding how local models travel in space and time, accurate predictions might be made.
To find out how disease travels, first one must know how people travel.
The problem is that travel occurs at all scales. There are local means of travel. Following a 2004 conference in Montreal, Brockmann was thinking about how he could model travel using aviation. He was concerned about how a mathematical model might be applied.
Talking with and old friend, who pointed to "wheresgeorge.com," gave him an idea. Wheresgeorge.com tracks how dollar bills move about. Brockmann believed that in principle, the method might be applied to how people travel and spread influenza. There was enough data already being collected by the site. Anyone could do the initial data entry, so the data was also spread out all over the country.
In other words, the data set was also large enough to come to valid statistical conclusions.
Going a bit deeper into the math, he displays a histogram, which shows a regular decay in the rate of movement that, which again, could modeled mathematically. It's a power law. The scaling laws imply that what follows is scale-free, meaning there would be no typical size.
Another example of scale free geometry is a fractal. How does this apply to how dollar bills travel?
After a long time of randomness, a levy flight will eventually emerge. The also occurs recursively inside the levy flight. Scale free movements of dollar bills means that there is a whole new mathematics that must be applied to the problem.
In complex network theory, there is an effort to describe other, human, relationships, such as those between friends.
By mapping communities, a community between New York and Los Angles can be easily demonstrated. The transportation which is used as a proxy can identify what effectively are the communities in the United States. He showed regional groups as identified by the census and what his research had revealed.
So what can one do with the data obtained? He showed a very effective difference between how a disease spread 200 years ago and now. Today, propagation is much much faster. It's more distributed, complex and fractal-like. It does not, as the first illustration shows, move in a predictable way from the east to the west coast.
He thanked the creator of wheresgeorge.com in conclusion.
He concludes by saying that ideas cannot be forced, they often occur coincidentally. Science takes courage and sometimes, a lack of knowledge of the problem you tackle. As an physicist tackling epidemiology, he benefited from that.
This has been frankly a difficult subject for me to follow. I'd encourage you to read others' take on his presentation.