May
01
2009

## Predicting flu cases and locations

A research group led by Dirk Brockmann at Northwestern University has created a computer model that predicts the spread of the 2009 H1N1 influenza virus in the US. (It uses a complex set of mathematical equations to describe the movement of people and virus.)

How can you track and predict the movement of something so small?: Follow the money, of course! (This is a colorized negative stained transmission electron micrograph (TEM) showing some of the ultrastructural morphology of the A/CA/4/09 swine flu virus. Got that? Good.Courtesy CDC/C.S. Goldsmith and A. Balish

(Brockmann was a guest on Minnesota Public Radio's Midmorning show today, and you can listen to it online.)

The good news is that, based on what we know now, and assuming that no one takes any preventive measures, we could expect to see some 1,700 cases of swine flu in the next four weeks. Because of the preventive measures being taken wherever a suspected case of H1N1 flu has popped up, we should actually see fewer cases. (You can see Brockmann's models here.) That's lousy if you're one of the folks who picks up the virus, but not a devastating number of cases. Of course, this is a rapidly developing, fluid situation, and things may change. Still, tools like Brockmann's model help to ensure that emergency supplies and other resources get to the places likely to need them most before they're needed.

Don't have faith in computer models? Well, a second research group at Indiana University is using another model, with different equations, and getting very similar results. That's a pretty good indication that the predictions are reliable.

You might remember Brockmann from a 2006 study that used data from WheresGeorge.com, a site that allows users to enter the serial numbers from their dollar bills in order to see where they go, to predict the probability of a given bill remaining within a 10km radius over time. That gave him a very good picture of human mobility, reflecting daily commuting traffic, intermediate traffic, and long-distance air travel, all of which help to model how a disease could spread.