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.
This fall, Robert Reinhart of Boston University published a study finding that electrical stimulation can boost memory - and Reinhart was surprised to discover the effects lasted a full month.
Scientists believe brain circuits tend to uncouple as we age. Since brain neurons communicate by exchanging electrical impulses with each other, the breakdown of these links and associations could be what causes the “senior moment”—when you can’t remember the name of the movie you just watched.
In 2019, Boston University researchers led by Robert Reinhart, director of the Cognitive and Clinical Neuroscience Laboratory, showed that memory loss in healthy older adults is likely caused by these disconnected brain networks. When Reinhart and his team stimulated two key areas of the brain with mild electrical current, they were able to bring the brains of older adult subjects back into sync — enough so that their ability to remember small differences between two images matched that of much younger subjects for at least 50 minutes after the testing stopped.
Reinhart wowed the neuroscience community once again this fall. His newer study in Nature Neuroscience presented 150 healthy participants, ages 65 to 88, who were able to recall more words on a given list after 20 minutes of low-intensity electrical stimulation sessions over four consecutive days. This amounted to a 50 to 65 percent boost in their recall.
Even Reinhart was surprised to discover the enhanced performance of his subjects lasted a full month when they were tested again later. Those who benefited most were the participants who were the most forgetful at the start.
An older person participates in Robert Reinhart's research on brain stimulation.
Robert Reinhart
Reinhart’s subjects only suffered normal age-related memory deficits, but NIBS has great potential to help people with cognitive impairment and dementia, too, says Krista Lanctôt, the Bernick Chair of Geriatric Psychopharmacology at Sunnybrook Health Sciences Center in Toronto. Plus, “it is remarkably safe,” she says.
Lanctôt was the senior author on a meta-analysis of brain stimulation studies published last year on people with mild cognitive impairment or later stages of Alzheimer’s disease. The review concluded that magnetic stimulation to the brain significantly improved the research participants’ neuropsychiatric symptoms, such as apathy and depression. The stimulation also enhanced global cognition, which includes memory, attention, executive function and more.
This is the frontier of neuroscience.
The two main forms of NIBS – and many questions surrounding them
There are two types of NIBS. They differ based on whether electrical or magnetic stimulation is used to create the electric field, the type of device that delivers the electrical current and the strength of the current.
Transcranial Current Brain Stimulation (tES) is an umbrella term for a group of techniques using low-wattage electrical currents to manipulate activity in the brain. The current is delivered to the scalp or forehead via electrodes attached to a nylon elastic cap or rubber headband.
Variations include how the current is delivered—in an alternating pattern or in a constant, direct mode, for instance. Tweaking frequency, potency or target brain area can produce different effects as well. Reinhart’s 2022 study demonstrated that low or high frequencies and alternating currents were uniquely tied to either short-term or long-term memory improvements.
Sessions may be 20 minutes per day over the course of several days or two weeks. “[The subject] may feel a tingling, warming, poking or itching sensation,” says Reinhart, which typically goes away within a minute.
The other main approach to NIBS is Transcranial Magnetic Simulation (TMS). It involves the use of an electromagnetic coil that is held or placed against the forehead or scalp to activate nerve cells in the brain through short pulses. The stimulation is stronger than tES but similar to a magnetic resonance imaging (MRI) scan.
The subject may feel a slight knocking or tapping on the head during a 20-to-60-minute session. Scalp discomfort and headaches are reported by some; in very rare cases, a seizure can occur.
No head-to-head trials have been conducted yet to evaluate the differences and effectiveness between electrical and magnetic current stimulation, notes Lanctôt, who is also a professor of psychiatry and pharmacology at the University of Toronto. Although TMS was approved by the FDA in 2008 to treat major depression, both techniques are considered experimental for the purpose of cognitive enhancement.
“One attractive feature of tES is that it’s inexpensive—one-fifth the price of magnetic stimulation,” Reinhart notes.
Don’t confuse either of these procedures with the horrors of electroconvulsive therapy (ECT) in the 1950s and ‘60s. ECT is a more powerful, riskier procedure used only as a last resort in treating severe mental illness today.
Clinical studies on NIBS remain scarce. Standardized parameters and measures for testing have not been developed. The high heterogeneity among the many existing small NIBS studies makes it difficult to draw general conclusions. Few of the studies have been replicated and inconsistencies abound.
Scientists are still lacking so much fundamental knowledge about the brain and how it works, says Reinhart. “We don’t know how information is represented in the brain or how it’s carried forward in time. It’s more complex than physics.”
Lanctôt’s meta-analysis showed improvements in global cognition from delivering the magnetic form of the stimulation to people with Alzheimer’s, and this finding was replicated inan analysis in the Journal of Prevention of Alzheimer’s Disease this fall. Neither meta-analysis found clear evidence that applying the electrical currents, was helpful for Alzheimer’s subjects, but Lanctôt suggests this might be merely because the sample size for tES was smaller compared to the groups that received TMS.
At the same time, London neuroscientist Marco Sandrini, senior lecturer in psychology at the University of Roehampton, critically reviewed a series of studies on the effects of tES on episodic memory. Often declining with age, episodic memory relates to recalling a person’s own experiences from the past. Sandrini’s review concluded that delivering tES to the prefrontal or temporoparietal cortices of the brain might enhance episodic memory in older adults with Alzheimer’s disease and amnesiac mild cognitive impairment (the predementia phase of Alzheimer’s when people start to have symptoms).
Researchers readily tick off studies needed to explore, clarify and validate existing NIBS data. What is the optimal stimulus session frequency, spacing and duration? How intense should the stimulus be and where should it be targeted for what effect? How might genetics or degree of brain impairment affect responsiveness? Would adjunct medication or cognitive training boost positive results? Could administering the stimulus while someone sleeps expedite memory consolidation?
Using MRI or another brain scan along with computational modeling of the current flow, a clinician could create a treatment that is customized to each person’s brain.
While Sandrini’s review reported improvements induced by tES in the recall or recognition of words and images, there is no evidence it will translate into improvements in daily activities. This is another question that will require more research and testing, Sandrini notes.
Scientists are still lacking so much fundamental knowledge about the brain and how it works, says Reinhart. “We don’t know how information is represented in the brain or how it’s carried forward in time. It’s more complex than physics.”
Where the science is headed
Learning how to apply precision medicine to NIBS is the next focus in advancing this technology, says Shankar Tumati, a post-doctoral fellow working with Lanctôt.
There is great variability in each person’s brain anatomy—the thickness of the skull, the brain’s unique folds, the amount of cerebrospinal fluid. All of these structural differences impact how electrical or magnetic stimulation is distributed in the brain and ultimately the effects.
Using MRI or another brain scan along with computational modeling of the current flow, a clinician could create a treatment that is customized to each person’s brain, from where to put the electrodes to determining the exact dose and duration of stimulation needed to achieve lasting results, Sandrini says.
Above all, most neuroscientists say that largescale research studies over long periods of time are necessary to confirm the safety and durability of this therapy for the purpose of boosting memory. Short of that, there can be no FDA approval or medical regulation for this clinical use.
Lanctôt urges people to seek out clinical NIBS trials in their area if they want to see the science advance. “That is how we’ll find the answers,” she says, predicting it will be 5 to 10 years to develop each additional clinical application of NIBS. Ultimately, she predicts that reigning in Alzheimer’s disease and mild cognitive impairment will require a multi-pronged approach that includes lifestyle and medications, too.
Sandrini believes that scientific efforts should focus on preventing or delaying Alzheimer’s. “We need to start intervention earlier—as soon as people start to complain about forgetting things,” he says. “Changes in the brain start 10 years before [there is a problem]. Once Alzheimer’s develops, it is too late.”
