In addition to genome sequencing, researchers questioned patients about the people they lived with and worked with, as well as where they spent their time, creating a network diagram of potential interactions. “Instead of just getting a list of names, you’re getting names, places, and behaviors, and you can paint a much more detailed picture of the underlying community structure,” says Gardy. “Key people and places and certain behaviors that might be contributing to an outbreak’s spread become much more apparent, and allow you to adjust your outbreak investigation in real-time as this new information becomes available.”
The researchers could overlay the genetic data identifying individual mutations with information from the social network that pinpointed when different people might have interacted with each other. “We could identify super-spreaders of the disease,” says Tang.
The researchers ultimately concluded that the outbreak was linked to an increase in crack cocaine use in the community. “That was the most likely trigger, reactivating latent disease and facilitating the spread of disease,” says Tang. Using this information, public health agencies could focus their resources on the root of the problem and identify those at the highest risk for reactivation of TB, he says.
“The findings show that it is feasible to combine genetic data and social structure to give an idea of the transmission chain and to distinguish two outbreaks going on at the same time,” says Joel Miller, a research fellow in the Center for Communicable Disease Dynamics at the Harvard School of Public Health.
Tang and others predict that this approach will become commonplace in the next few years. “With the cost of whole-genome sequencing coming down—it’s a few hundred dollars per organism—a lot of people are interested in using it to address questions worldwide,” says Tang. He says sequencing will be especially important in more complex cases, such as tracking the spread of antibiotic-resistant organisms around the world.
The main hurdle now is not the cost of sequencing, but rather the analysis tools, adds Tang. “The limitation for most people is how to make sense of the genomic data that is generated,” he says.