In 2008, Google launched “Flu Trends.” It was an attempt to track the spread of influenza based on “aggregated search queries.” According to a 2015 blog post, Google Flu Trends will no longer continue with its own website. Rather, it will be providing data directly to infectious disease researchers at institutions like Columbia University’s Mailman School of Public Health. One of those researchers is Jeffrey Shaman. He lead a team that won the Centers for Disease Control and Prevention “Predict the Influenza Season Challenge” last year by creating a flu forecast. Much like a weather forecast that predicts a 70 percent chance of rain, for example, Shaman’s models sought to predict a 70 percent chance of influenza.

Meanwhile, Rumi Chunara, who works across fields like public health and computer science at New York University, is also looking to map the spread of the flu, but at a more granular level. As a part of the GoViral study, she collects fluid specimens—such as saliva and nasal swabs—to track who has the flu, and who in the surrounding community is at risk for getting it. Chunara and Shaman join Ira to talk about how we’re getting better at predicting the flu and how our improvement can help us combat it.