Mapping drug addicts’ tracks

WASHINGTON — Here at the annual meeting of the Association of American Geographers, there’s a lot of map talk. People are proudly showing off maps of land rights, maps of cloud formation, even maps of how teenagers form herds in malls.

But to me, one of the most compelling maps traced the steps of a single man, a drug addict, as he traveled through Baltimore.

The man carried a GPS unit, given to him by clinicians who were treating him at a methadone clinic. The unit, about the size of a thick domino, tracked his motion every time he moved 25 meters, or every 25 minutes if he was still.  

The researchers also gave the man a handheld personal digital assistant, or PDA, so that he could answer questions about his drug use. At four random times every day, the PDA would beep, prompting him to answer multiple-choice questions about his state of mind. He would also turn the PDA on and answer questions each time he used drugs.  Over the course of 18 weeks, a team of researchers including David Epstein of the National Institute on Drug Abuse in Baltimore collected the data from the PDA and lined it up with the man’s geographical position. Epstein presented the team’s preliminary results April 14.

Squiggly lines traced the man’s path as he wended around the city and out into the surrounding suburbs. Black dots pinpointed the places along the way where the man had used drugs. In the preliminary research, the scientists have plotted factors such as violence rates, wealth, liquor store prevalence, employment and race onto the map of Baltimore. For the most part, the man spent most of his time in relatively nice neighborhoods, such as the Inner Harbor. But the places riddled with black dots — where he used drugs — were by and large the worst parts of town.

The link between rough neighborhoods and drug addiction is strong, other studies have shown. “Addiction is a brain disease, but it is other things too,” Epstein said. One study Epstein mentioned was particularly compelling: The people most likely to try illegal drugs are white, middle- or upper-class, and educated. The people most likely to get addicted to the drugs are not any of those.

Understanding just how powerful bad neighborhoods are for feeding addiction might lead to better ways to fight it. For instance, studies have shown that people who move out of bad neighborhoods are more likely to stay clean.

Epstein and his colleagues hope to add a potentially valuable tool for fighting the addiction problem by watching individuals’ steps. Currently, the team has enrolled just 25 people in the study but plans to ultimately enroll 125. So far, the drug users have been good about logging the data and returning to the methadone clinic with the devices, Epstein said.

With a larger dataset, the team wants to start asking questions about people’s travels, such as whether people who spend time in more areas are better able to stay clean, whether addicts’ movements change with treatment, and whether on-the-spot interventions might cut the chances of relapse. Addiction spurred by grim living situations might ultimately be curbed by improving the hardest-hit neighborhoods and “giving people reasons not to get addicted,” Epstein said.