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.
Researchers have found that a mindfulness-based therapy, including savoring natural rewards, can help patients with chronic pain and opioid addiction.
Garland’s study focused on 250 adults who had received opioid therapy for chronic pain for 90 days or longer, randomly assigning them to eight weeks of either a standard psychotherapy support group or Mindfulness-Oriented Recovery Enhancement (MORE) therapy, which combines mindfulness training, cognitive-behavioral therapy (CBT) and positive psychology. Nine months after getting these treatments in primary care settings, 45 percent of patients in the MORE group were no longer misusing opioids, compared to 24 percent of those in group therapy. In fact, about a third of the patients in the MORE group were able to cut their opioid dose in half or reduce it even further.
Patients treated with MORE also experienced more significant pain relief than those in support groups, according to Garland. Conventional approaches to treating opioid addiction include 12-step programs and medically-assisted treatment using drugs like methadone and Suboxone, sometimes coupled with support groups. But patients with Opioid Use Disorder (OUD) – the official diagnosis for opioid addiction – have high relapse rates following treatment, especially if they have chronic pain.
While medically-assisted treatments help to control drug cravings, they do nothing to control chronic pain, which is where psychological therapies like MORE come in.
“For patients suffering from moderate pain and OUD, the relapse rate is three times higher than in patients without chronic pain; for those with severe chronic pain, the relapse rate is five times higher,” says Amy Wachholtz, PhD, Director of Clinical Health Psychology and associate professor at University of Colorado in Denver. “So if we don’t treat the chronic pain along with the OUD addiction simultaneously, we are setting patients up for failure.”
Unfortunately, notes Garland, the standard of care for patients with chronic pain who are misusing their prescribed painkillers is “woefully inadequate.” Many patients don’t meet the criteria for OUD, he says, but instead fall into a gray zone somewhere between legitimate opioid use and full-blown addiction. And while medically-assisted treatments help to control drug cravings, they do nothing to control chronic pain, which is where psychological therapies like MORE come in. But behavioral therapies are often not available in primary care settings, and even when clinicians do refer patients to behavioral health providers, they often prescribe CBT. A large scale study last year showed that CBT – without the added components of mindfulness training and positive psychology – reduced pain but not opioid misuse.
Psychotherapist Eric Garland teaches mindfulness.
University of Utah
Reward Circuitry Rewired
Opioids are highly physiologically addictive. Repeated and high-dose drug use causes the brain to become hypersensitive to stress, pain, and drug-related cues, such as the sight of one’s pill bottle, says Garland, while at the same time becoming increasingly insensitive to natural pleasures. “As an individual becomes more and more dependent on the opioids just to feel okay, they feel less able to extract a healthy sense of joy, pleasure and meaning out of everyday life,” he explains. “This drives them to take higher and higher doses of the opioid to maintain a dwindling sense of well-being.”
The changes are not just psychological: Chronic opioid use actually causes changes in the brain’s reward circuitry. “You can see on brain imaging,” says Garland. “The brain’s reward circuitry becomes more responsive when a person is viewing opioid related images than when they are viewing images of smiling babies, lovers holding hands, or sunsets over the beach.” MORE, he says, teaches “savoring” – a tenet of positive psychology – as a means of restructuring the reward processes in the brain so the patient becomes sensitive to pleasure from natural, healthy rewards, decreasing cravings for drug-related rewards.
Mindfulness and Addiction
Mindfulness, a form of meditation that teaches people to observe their feelings and sensations without judgement, has been increasingly applied to the treatment of addiction. By observing their pain and cravings objectively, for example, patients gain increased awareness of their responses to pain and their habits of opioid use. “They learn how to be with discomfort, whether emotional or physical, in a more compassionate way,” says Sarah Bowen, PhD, associate professor of psychology at Pacific University in Oregon. “And if your mind gives you a message like ‘Oh, I can’t handle that,’ to recognize that that’s a thought that might not be true.”
Bowen’s research is focused on Mindfulness-Based Relapse Prevention, which addresses the cravings associated with addiction. She has patients practice what she calls “urge surfing”: riding out a craving or urge rather than relying on a substance for immediate relief. “Craving will happen, so rather than fighting it, we look at understanding it better,” she says.
MORE differs from other forms of mindfulness-based therapy in that it integrates reappraisal and savoring training. Reappraisal is a technique often used in CBT in which patients learn to change negative thought patterns in order to reduce their emotional impact, while savoring helps to restructure the reward processes in the brain.
Mindfulness training not only helps patients to understand and gain control over their behavior in response to cravings and triggers like pain, says Garland, but also provides a means of pain relief. “We use mindfulness to zoom into pain and break it down into its subcomponents – feelings of heat or tightness or tingling – which reduces the impact that negative emotions have on pain processing in the brain.”
Eric Garland examines brain waves.
University of Utah
Powerful interventions
As the dangers of opioid addiction have become increasingly evident, some scientists are developing less addictive, non-opioid painkillers, but more trials are needed. Meanwhile, behavioral approaches to chronic pain relief have continued to gain traction, and researchers like Garland are probing the possibilities of integrative treatments to treat the addiction itself. Given that the number of people suffering from chronic pain and OUD have reached new heights during the COVID-19 pandemic, says Wachholtz, new treatment alternatives for patients caught in the relentless cycle of chronic pain and opioid misuse are sorely needed. “We’re trying to refine the techniques,” she says, “but we’re starting to realize just how powerful some of these mind-body interventions can be.”
