Lalith Polepeddi is working to reduce the impacts of pandemics, and hopes one day to find ways to avoid them altogether.
Students of Global Health 301: Introduction to International Public Health had the chance Thursday morning to talk to alumnus and researcher Lalith Polepeddi about his work tracking and preventing epidemics.
The talk, which took place in Northwestern’s Frances Searle building and was attended by about 40 students, focused on Polepeddi’s work at Global Viral Forecasting, a San Francisco non-profit whose stated purpose is develop a global system to prevent pandemics. And how are they doing that?
With data.
“Our goal is to detect, track and forecast all outbreaks around the world,” said Polepeddi, who majored in biological sciences and computer science. The project, named EpidemicIQ, is part of the Global Virus Forecasting Initiative’s overall mission to reduce the amount of time between an outbreak and its spread.
“Dramatic failures in such pandemic control, such as the ongoing lack of success in HIV vaccine development twenty-five years into the pandemic, have shown that this wait-and-respond approach is not sufficient,” states the GVFI’s website.
It is this lag – of often two weeks, Polepeddi said – that he and others in his field find agonizing. A direct result of the fact that epidemics seem always to catch people by surprise, the lag prevents immediate action and creates spending waste. Polepeddi wants to change this “reactive” state of global health to a “predictive” one.
To do this, he and fellow researchers collect the kinds of data that can inform them about the spread of disease. Sometimes this means medical information, but sometimes this simply means mobile phone records, or information from blogs, Facebook, Twitter.
“The majority of the world is already connected via mobile phones,” he said, explaining that mapping phone records can paint a picture of who is connected to whom, and therefore of the lines along with a pandemic is likely to spread.
Collecting phone data, in other words, is an accurate measure of mobility. So if there were news of an outbreak in the Democratic Republic of Congo, for example, scientists and global health workers could use phone records to overlay a network and predict along which lines the disease would spread.
“It’s a little bit creepy,” he jokes, “but if it’s anonymized we should be able to make use of it.”
This is one way to move from away from a reactive model and toward a predictive one. Unfortunately, changing the current state of affairs is not that easy.
For one thing, information can sometimes be hard to come by. While news outlets and the Internet are viable sources of information in many locales around the world, in many they are not. Records from doctors visits would be useful indeed, but are largely unavailable due to doctor-patient confidentiality. Language barriers can also be a problem.
Nonetheless, said Elizabeth Barden, who teaches the class, utilizing technology to its full potential – and especially in the ever-crucial realm of public health – is more important now than ever.
“Harnessing it efficiently and effectively is so important,” she said, adding that Polepeddi’s approach could help students find ways to make a difference that don’t start with an MD.
“There’s such a need for this kind of work in global health and the applications are huge,” she said. “For students it reinforces the point that you don’t need to be a physician to make a big impact.”
