A future app may help you avoid getting the flu by informing you of your local risk on a given day.
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.
Amber Freed and Maxwell near their home in Denver, Colorado.
Getting the diagnosis took months of painful, invasive procedures, as well as fighting with the health insurance to get the genetic testing approved. Finally, in June 2018, doctors at the Children's Hospital Colorado gave the Freeds their son's diagnosis—a genetic mutation so rare it didn't even have a name, just a bunch of letters jammed together into a word SLC6A1—same as the name of the mutated gene. The mutation, with only 40 cases known worldwide at the time, caused developmental disabilities, movement and speech disorders, and a debilitating form of epilepsy.
The doctors didn't know much about the disorder, but they said that Maxwell would also regress in his development when he turned three or four. They couldn't tell how long he would live. "Hopefully you would become an expert and educate us about it," they said, as they gave Freed a five-page paper on the SLC6A1 and told her to start calling scientists if she wanted to help her son in any way. When she Googled the name, nothing came up. She felt horrified. "Our disease was too rare to care."
Freed's husband, a 6'2'' college football player broke down in sobs and she realized that if anything could be done to help Maxwell, she'd have be the one to do it. "I understood that I had to fight like a mother," she says. "And a determined mother can do a lot of things."
The Freed family.
Courtesy Amber Freed
She quit her job as an equity analyst the day of the diagnosis and became a full-time SLC6A1 citizen scientist looking for researchers studying mutations of this gene. In the wee hours of the morning, she called scientists in Europe. As the day progressed, she called researchers on the East Coast, followed by the West in the afternoon. In the evening, she switched to Asia and Australia. She asked them the same question. "Can you help explain my gene and how do we fix it?"
Scientists need money to do research, so Freed launched Milestones for Maxwell fundraising campaign, and a SLC6A1 Connect patient advocacy nonprofit, dedicated to improving the lives of children and families battling this rare condition. And then it became clear that the mutation wasn't as rare as it seemed. As other parents began to discover her nonprofit, the number of known cases rose from 40 to 100, and later to 400, Freed says. "The disease is only rare until it messes with the wrong mother."
It took one mother to find another to start looking into what's happening inside Maxwell's brain. Freed came across Jeanne Paz, a Gladstone Institutes researcher who studies epilepsy with particular interest in absence or silent seizures—those that don't manifest by convulsions, but rather make patients absently stare into space—and that's one type of seizures Maxwell has. "It's like a brief period of silence in the brain during which the person doesn't pay attention to what's happening, and as soon as they come out of the seizure they are back to life," Paz explains. "It's like a pause button on consciousness." She was working to understand the underlying biology.
To understand how seizures begin, spread and stop, Paz uses optogenetics in mice. From words "genetic" and "optikós," which means visible in Greek, the optogenetics technique involves two steps. First, scientists introduce a light-sensitive gene into a specific brain cell type—for example into excitatory neurons that release glutamate, a neurotransmitter, which activates other cells in the brain. Then they implant a very thin optical fiber into the brain area where they forged these light-sensitive neurons. As they shine the light through the optical fiber, researchers can make excitatory neurons to release glutamate—or instead tell them to stop being active and "shut up". The ability to control what these neurons of interest do, quite literally sheds light onto where seizures start, how they propagate and what cells are involved in stopping them.
"Let's say a seizure started and we shine the light that reduces the activity of specific neurons," Paz explains. "If that stops the seizure, we know that activating those cells was necessary to maintain the seizure." Likewise, shutting down their activity will make the seizure stop.
Freed reached out to Paz in 2019 and the two women had an instant connection. They were both passionate about brain and seizures research, even if for different reasons. Freed asked Paz if she would study her son's seizures and Paz agreed.
To do that, Paz needed mice that carried the SLC6A1 mutation, so Freed found a company in China that created them to specs. The company replaced a mouse SLC6A1 gene with a human mutated one and shipped them over to Paz's lab. "We call them Maxwell mice," Paz says, "and we are now implanting electrodes into them to see which brain regions generate seizures." That would help them understand what goes wrong and what brain cells are malfunctioning in the SLC6A1 mice—and help scientists better understand what might cause seizures in children.
Bred to carry SLC6A1 mutation, these "Maxwell mice" will help better understand this debilitating genetic disease. (These mice are from Vanderbilt University, where researchers are also studying SLC6A1.)
Courtesy Amber Freed
This information—along with other research Amber is funding in other institutions—will inform the development of a novel genetic treatment, in which scientists would deploy a harmless virus to deliver a healthy, working copy of the SLC6A1 gene into the mice brains. They would likely deliver the therapeutic via a spinal tap infusion, and if it works and doesn't produce side effects in mice, the human trials will follow.
In the meantime, Freed is raising money to fund other research of various stop-gap measures. On April 22, 2021, she updated her Milestone for Maxwell page with a post that her nonprofit is funding yet another effort. It is a trial at Weill Cornell Medicine in New York City, in which doctors will use an already FDA-approved drug, which was recently repurposed for the SLC6A1 condition to treat epilepsy in these children. "It will buy us time," Freed says—while the gene therapy effort progresses.
Freed is determined to beat SLC6A1 before it beats down her family. She hopes to put an end to this disease—and similar genetic diseases—once and for all. Her goal is not only to have scientists create a remedy, but also to add the mutation to a newborn screening panel. That way, children born with this condition in the future would receive gene therapy before they even leave the hospital.
"I don't want there to be another Maxwell Freed," she says, "and that's why I am fighting like a mother." The gene therapy trial still might be a few years away, but the Weill Cornell one aims to launch very soon—possibly around Mother's Day. This is yet another milestone for Maxwell, another baby step forward—and the best gift a mother can get.