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.
She figured the pain would go away. But instead, it intensified that night. Kamil's husband drove her to the Cedars-Sinai hospital, where she was admitted to the coronary care unit. It turned out she wasn't having a heart attack after all. Instead, she was diagnosed with a much less common but nonetheless dangerous heart condition called takotsubo syndrome, or broken heart syndrome.
A heart attack happens when blood flow to the heart is obstructed—such as when an artery is blocked—causing heart muscle tissue to die. In takotsubo syndrome, the blood flow isn't blocked, but the heart doesn't pump it properly. The heart changes its shape and starts to resemble a Japanese fishing device called tako-tsubo, a clay pot with a wider body and narrower mouth, used to catch octopus.
"The heart muscle is stunned and doesn't function properly anywhere from three days to three weeks," explains Noel Bairey Merz, the cardiologist at Cedar Sinai who Kamil went to see after she was discharged.
"The heart muscle is stunned and doesn't function properly anywhere from three days to three weeks."
But even though the heart isn't permanently damaged, mortality rates due to takotsubo syndrome are comparable to those of a heart attack, Merz notes—about 4-5 percent of patients die from the attack, and 20 percent within the next five years. "It's as bad as a heart attack," Merz says—only it's much less known, even to doctors. The condition affects only about 1 percent of people, and there are around 15,000 new cases annually. It's diagnosed using a cardiac ventriculogram, an imaging test that allows doctors to see how the heart pumps blood.
Scientists don't fully understand what causes Takotsubo syndrome, but it usually occurs after extreme emotional or physical stress. Doctors think it's triggered by a so-called catecholamine storm, a phenomenon in which the body releases too much catecholamines—hormones involved in the fight-or-flight response. Evolutionarily, when early humans lived in savannas or forests and had to either fight off predators or flee from them, these hormones gave our ancestors the needed strength and stamina to take either action. Released by nerve endings and by the adrenal glands that sit on top of the kidneys, these hormones still flood our bodies in moments of stress, but an overabundance of them could sometimes be damaging.
Elaine Kamil
A study by scientists at Harvard Medical School linked increased risk of takotsubo to higher activity in the amygdala, a brain region responsible for emotions that's involved in responses to stress. The scientists believe that chronic stress makes people more susceptible to the syndrome. Notably, one small study suggested that the number of Takotsubo cases increased during the COVID-19 pandemic.
There are no specific drugs to treat takotsubo, so doctors rely on supportive therapies, which include medications typically used for high blood pressure and heart failure. In most cases, the heart returns to its normal shape within a few weeks. "It's a spontaneous recovery—the catecholamine storm is resolved, the injury trigger is removed and the heart heals itself because our bodies have an amazing healing capacity," Merz says. It also helps that tissues remain intact. 'The heart cells don't die, they just aren't functioning properly for some time."
That's the good news. The bad news is that takotsubo is likely to strike again—in 5-20 percent of patients the condition comes back, sometimes more severe than before.
That's exactly what happened to Kamil. After getting her diagnosis in 2013, she realized that she actually had a previous takotsubo episode. In 2010, she experienced similar symptoms after her son died. "The night after he died, I was having severe chest pain at night, but I was too overwhelmed with grief to do anything about it," she recalls. After a while, the pain subsided and didn't return until three years later.
For weeks after her second attack, she felt exhausted, listless and anxious. "You lose confidence in your body," she says. "You have these little twinges on your chest, or if you start having arrhythmia, and you wonder if this is another episode coming up. It's really unnerving because you don't know how to read these cues." And that's very typical, Merz says. Even when the heart muscle appears to recover, patients don't return to normal right away. They have shortens of breath, they can't exercise, and they stay anxious and worried for a while.
Women over the age of 50 are diagnosed with takotsubo more often than other demographics. However, it happens in men too, although it typically strikes after physical stress, such as a triathlon or an exhausting day of cycling. Young people can also get takotsubo. Older patients are hospitalized more often, but younger people tend to have more severe complications. It could be because an older person may go for a jog while younger one may run a marathon, which would take a stronger toll on the body of a person who's predisposed to the condition.
Notably, the emotional stressors don't always have to be negative—the heart muscle can get out of shape from good emotions, too. "There have been case reports of takotsubo at weddings," Merz says. Moreover, one out of three or four takotsubo patients experience no apparent stress, she adds. "So it could be that it's not so much the catecholamine storm itself, but the body's reaction to it—the physiological reaction deeply embedded into out physiology," she explains.
Merz and her team are working to understand what makes people predisposed to takotsubo. They think a person's genetics play a role, but they haven't yet pinpointed genes that seem to be responsible. Genes code for proteins, which affect how the body metabolizes various compounds, which, in turn, affect the body's response to stress. Pinning down the protein involved in takotsubo susceptibility would allow doctors to develop screening tests and identify those prone to severe repeating attacks. It will also help develop medications that can either prevent it or treat it better than just waiting for the body to heal itself.
Researchers at the Imperial College London found that elevated levels of certain types of microRNAs—molecules involved in protein production—increase the chances of developing takotsubo.
In one study, researchers tried treating takotsubo in mice with a drug called suberanilohydroxamic acid, or SAHA, typically used for cancer treatment. The drug improved cardiac health and reversed the broken heart in rodents. It remains to be seen if the drug would have a similar effect on humans. But identifying a drug that shows promise is progress, Merz says. "I'm glad that there's research in this area."
This article was originally published by Leaps.org on July 28, 2021.
