Scientists Are Building an “AccuWeather” for Germs to Predict Your Risk of Getting the Flu

Scientists Are Building an “AccuWeather” for Germs to Predict Your Risk of Getting the Flu

A future app may help you avoid getting the flu by informing you of your local risk on a given day.

(© Dmytro Flisak/Adobe)



Applied mathematician Sara del Valle works at the U.S.'s foremost nuclear weapons lab: Los Alamos. Once colloquially called Atomic City, it's a hidden place 45 minutes into the mountains northwest of Santa Fe. Here, engineers developed the first atomic bomb.

Like AccuWeather, an app for disease prediction could help people alter their behavior to live better lives.

Today, Los Alamos still a small science town, though no longer a secret, nor in the business of building new bombs. Instead, it's tasked with, among other things, keeping the stockpile of nuclear weapons safe and stable: not exploding when they're not supposed to (yes, please) and exploding if someone presses that red button (please, no).

Del Valle, though, doesn't work on any of that. Los Alamos is also interested in other kinds of booms—like the explosion of a contagious disease that could take down a city. Predicting (and, ideally, preventing) such epidemics is del Valle's passion. She hopes to develop an app that's like AccuWeather for germs: It would tell you your chance of getting the flu, or dengue or Zika, in your city on a given day. And like AccuWeather, it could help people alter their behavior to live better lives, whether that means staying home on a snowy morning or washing their hands on a sickness-heavy commute.

Sara del Valle of Los Alamos is working to predict and prevent epidemics using data and machine learning.

Since the beginning of del Valle's career, she's been driven by one thing: using data and predictions to help people behave practically around pathogens. As a kid, she'd always been good at math, but when she found out she could use it to capture the tentacular spread of disease, and not just manipulate abstractions, she was hooked.

When she made her way to Los Alamos, she started looking at what people were doing during outbreaks. Using social media like Twitter, Google search data, and Wikipedia, the team started to sift for trends. Were people talking about hygiene, like hand-washing? Or about being sick? Were they Googling information about mosquitoes? Searching Wikipedia for symptoms? And how did those things correlate with the spread of disease?

It was a new, faster way to think about how pathogens propagate in the real world. Usually, there's a 10- to 14-day lag in the U.S. between when doctors tap numbers into spreadsheets and when that information becomes public. By then, the world has moved on, and so has the disease—to other villages, other victims.

"We found there was a correlation between actual flu incidents in a community and the number of searches online and the number of tweets online," says del Valle. That was when she first let herself dream about a real-time forecast, not a 10-days-later backcast. Del Valle's group—computer scientists, mathematicians, statisticians, economists, public health professionals, epidemiologists, satellite analysis experts—has continued to work on the problem ever since their first Twitter parsing, in 2011.

They've had their share of outbreaks to track. Looking back at the 2009 swine flu pandemic, they saw people buying face masks and paying attention to the cleanliness of their hands. "People were talking about whether or not they needed to cancel their vacation," she says, and also whether pork products—which have nothing to do with swine flu—were safe to buy.

At the latest meeting with all the prediction groups, del Valle's flu models took first and second place.

They watched internet conversations during the measles outbreak in California. "There's a lot of online discussion about anti-vax sentiment, and people trying to convince people to vaccinate children and vice versa," she says.

Today, they work on predicting the spread of Zika, Chikungunya, and dengue fever, as well as the plain old flu. And according to the CDC, that latter effort is going well.

Since 2015, the CDC has run the Epidemic Prediction Initiative, a competition in which teams like de Valle's submit weekly predictions of how raging the flu will be in particular locations, along with other ailments occasionally. Michael Johannson is co-founder and leader of the program, which began with the Dengue Forecasting Project. Its goal, he says, was to predict when dengue cases would blow up, when previously an area just had a low-level baseline of sick people. "You'll get this massive epidemic where all of a sudden, instead of 3,000 to 4,000 cases, you have 20,000 cases," he says. "They kind of come out of nowhere."

But the "kind of" is key: The outbreaks surely come out of somewhere and, if scientists applied research and data the right way, they could forecast the upswing and perhaps dodge a bomb before it hit big-time. Questions about how big, when, and where are also key to the flu.

A big part of these projects is the CDC giving the right researchers access to the right information, and the structure to both forecast useful public-health outcomes and to compare how well the models are doing. The extra information has been great for the Los Alamos effort. "We don't have to call departments and beg for data," says del Valle.

When data isn't available, "proxies"—things like symptom searches, tweets about empty offices, satellite images showing a green, wet, mosquito-friendly landscape—are helpful: You don't have to rely on anyone's health department.

At the latest meeting with all the prediction groups, del Valle's flu models took first and second place. But del Valle wants more than weekly numbers on a government website; she wants that weather-app-inspired fortune-teller, incorporating the many diseases you could get today, standing right where you are. "That's our dream," she says.

This plot shows the the correlations between the online data stream, from Wikipedia, and various infectious diseases in different countries. The results of del Valle's predictive models are shown in brown, while the actual number of cases or illness rates are shown in blue.

(Courtesy del Valle)

The goal isn't to turn you into a germophobic agoraphobe. It's to make you more aware when you do go out. "If you know it's going to rain today, you're more likely to bring an umbrella," del Valle says. "When you go on vacation, you always look at the weather and make sure you bring the appropriate clothing. If you do the same thing for diseases, you think, 'There's Zika spreading in Sao Paulo, so maybe I should bring even more mosquito repellent and bring more long sleeves and pants.'"

They're not there yet (don't hold your breath, but do stop touching your mouth). She estimates it's at least a decade away, but advances in machine learning could accelerate that hypothetical timeline. "We're doing baby steps," says del Valle, starting with the flu in the U.S., dengue in Brazil, and other efforts in Colombia, Ecuador, and Canada. "Going from there to forecasting all diseases around the globe is a long way," she says.

But even AccuWeather started small: One man began predicting weather for a utility company, then helping ski resorts optimize their snowmaking. His influence snowballed, and now private forecasting apps, including AccuWeather's, populate phones across the planet. The company's progression hasn't been without controversy—privacy incursions, inaccuracy of long-term forecasts, fights with the government—but it has continued, for better and for worse.

Disease apps, perhaps spun out of a small, unlikely team at a nuclear-weapons lab, could grow and breed in a similar way. And both the controversies and public-health benefits that may someday spin out of them lie in the future, impossible to predict with certainty.

Sarah Scoles
Sarah Scoles is a freelance science journalist based in Denver. She is a contributing writer at Wired, a contributing editor at Popular Science, and the author of the book Making Contact: Jill Tarter and the Search for Extraterrestrial Intelligence.
Award-Winning Scientists Offer Advice to President Biden

The White House in Washington, D.C.

Unsplash

This article is part of the magazine, "The Future of Science In America: The Election Issue," co-published by LeapsMag, the Aspen Institute Science & Society Program, and GOOD.

We invited Nobel Prize, National Medal of Science, and Breakthrough Prize Laureates working in America to offer advice to the next President on how to prioritize science and medicine in the next four years. Almost universally, these 28 letters underscore the importance of government support for basic or fundamental research to fuel long-term solutions to challenges like infectious diseases, climate change, and environmental preservation.

Many of these scientists are immigrants to the United States and emphasize how they moved to this country for its educational and scientific opportunities, which recently have been threatened by changes in visa policies for students and researchers from overseas. Many respondents emphasize the importance of training opportunities for scientists from diverse backgrounds to ensure that America can continue to have one of the strongest, most creative scientific workforces in the world.

Keep Reading Keep Reading
Aaron F. Mertz
Aaron F. Mertz, Ph.D., is a biophysicist, science advocate, and the founding Director of the Aspen Institute Science & Society Program, launched in 2019 to help foster a diverse scientific workforce whose contributions extend beyond the laboratory and to generate greater public appreciation for science as a vital tool to address global challenges. He completed postdoctoral training in cell biology at Rockefeller University, a doctorate in physics at Yale University, a master’s degree in the history of science at the University of Oxford as a Rhodes Scholar, and a bachelor’s degree in physics at Washington University in St. Louis.
Out of Thin Air: A Fresh Solution to Farming’s Water Shortages

Dry, arid and remote farming regions are vulnerable to water shortages, but scientists are working on a promising new solution.

Photo by Amir Shahabi on Unsplash

California has been plagued by perilous droughts for decades. Freshwater shortages have sparked raging wildfires and killed fruit and vegetable crops. And California is not alone in its danger of running out of water for farming; parts of the Southwest, including Texas, are battling severe drought conditions, according to the North American Drought Monitor. These two states account for 316,900 of the 2 million total U.S. farms.

But even as farming becomes more vulnerable due to water shortages, the world's demand for food is projected to increase 70 percent by 2050, according to Guihua Yu, an associate professor of materials science at The University of Texas at Austin.

"Water is the most limiting natural resource for agricultural production because of the freshwater shortage and enormous water consumption needed for irrigation," Yu said.

Keep Reading Keep Reading
Katie Navarra
Katie Navarra is an award-winning writer who covers education, horses, farming, and business/leadership.