Scientists Are Building an “AccuWeather” for Germs to Predict Your Risk of Getting the Flu
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.
For millions of people with macular degeneration, treatment options are slim. The disease causes loss of central vision, which allows us to see straight ahead, and is highly dependent on age, with people over 75 at approximately 30% risk of developing the disorder. The BrightFocus Foundation estimates 11 million people in the U.S. currently have one of three forms of the disease.
Recently, ophthalmologists including Daniel Palanker at Stanford University published research showing advances in the PRIMA retinal implant, which could help people with advanced, age-related macular degeneration regain some of their sight. In a feasibility study, five patients had a pixelated chip implanted behind the retina, and three were able to see using their remaining peripheral vision and—thanks to the implant—their partially restored central vision at the same time.
Should people with macular degeneration be excited about these results?
“Every week, if not every day, patients come to me with this question because it's devastating when they lose their central vision,” says retinal surgeon Lynn Huang. About 40% of her patients have macular degeneration. Huang tells them that these implants, along with new medications and stem cell therapies, could be useful in the coming years.
“The goal here is to replace the missing photoreceptors with photovoltaic pixels, basically like little solar panels,” Palanker says.
That implant, a pixelated chip, works together with a tiny video camera on a specially designed pair of eyeglasses, which can be adjusted for each patient’s prescription. The video camera relays processed images to the chip, which electrically stimulates inner retinal neurons. These neurons, in turn, relay information to the brain’s visual cortex through the optic nerve. The chip restores patients’ central sight, but not completely. The artificial vision is basically monochromatic (whitish-yellowish) and fairly blurry; patients were still legally blind even after the implant, except when using a zoom function on the camera, but those with proper chip placement could make out large letters.
“The goal here is to replace the missing photoreceptors with photovoltaic pixels, basically like little solar panels,” Palanker says. These pixels, located on the implanted chip, convert light into pulsed electrical currents that stimulate retinal neurons. In time, Palanker hopes to improve the chips, resulting in bigger boosts to visual acuity.
The pixelated chips are surgically implanted during a process Palanker admits is still “a surgical learning curve.” In the study, three chips were implanted correctly, one was placed incorrectly, and another patient’s chip moved after the procedure; he did not follow post-surgical recommendations. One patient passed away during the study for unrelated reasons.
University of Maryland retinal specialist Kenneth Taubenslag, who was not involved in the study, said that subretinal surgeries have become less common in recent years, but expects implants to spur improvements in these techniques. “I think as people get more experience, [they’ll] probably get more reliable placement of the implant,” he said, pointing out that even the patient with the misplaced chip was able to gain some light perception, if not the same visual acuity as other patients.
Retinal implants have come under scrutiny lately. IEEE Spectrum reported that Second Sight, manufacturer of the Argus II implant used for people with retinitis pigmentosa, a genetic disease that causes vision loss, would no longer support the product. After selling hundreds of the implants at $150,000 apiece, company leaders announced they’d “decided to pursue an orderly wind down” of Second Sight in March 2020 in the wake of financial issues. Last month, the company announced a merger, shifting its focus to a new retinal implant, raising questions for patients who have Argus II implants.
Retinal surgeon Eugene de Juan of the University of California, San Francisco, was involved with early studies of the Argus implants, though his participation ended over a decade ago, before the device was marketed by Second Sight. He says he would consider recommending future implants to patients with macular degeneration, given the promise of the technology and the lack of other alternatives.
“I tell my patients that this is an area of active research and development, and it's getting better and better, so let's not give up hope,” de Juan says. He believes cautious optimism for Palanker’s implant is appropriate: “It's not the first, it's not the only, but it's a good approach with a good team.”
How dozens of men across Alaska (and their dogs) teamed up to save one town from a deadly outbreak
During the winter of 1924, Curtis Welch – the only doctor in Nome, a remote fishing town in northwest Alaska – started noticing something strange. More and more, the children of Nome were coming to his office with sore throats.
Initially, Welch dismissed the cases as tonsillitis or some run-of-the-mill virus – but when more kids started getting sick, with some even dying, he grew alarmed. It wasn’t until early 1925, after a three-year-old boy died just two weeks after becoming ill, that Welch realized that his worst suspicions were true. The boy – and dozens of other children in town – were infected with diphtheria.
A DEADLY BACTERIA
Diphtheria is nearly nonexistent and almost unheard of in industrialized countries today. But less than a century ago, diphtheria was a household name – one that struck fear in the heart of every parent, as it was extremely contagious and particularly deadly for children.
Diphtheria – a bacterial infection – is an ugly disease. When it strikes, the bacteria eats away at the healthy tissues in a patient’s respiratory tract, leaving behind a thick, gray membrane of dead tissue that covers the patient's nose, throat, and tonsils. Not only does this membrane make it very difficult for the patient to breathe and swallow, but as the bacteria spreads through the bloodstream, it causes serious harm to the heart and kidneys. It sometimes also results in nerve damage and paralysis. Even with treatment, diphtheria kills around 10 percent of people it infects. Young children, as well as adults over the age of 60, are especially at risk.
Welch didn’t suspect diphtheria at first. He knew the illness was incredibly contagious and reasoned that many more people would be sick – specifically, the family members of the children who had died – if there truly was an outbreak. Nevertheless, the symptoms, along with the growing number of deaths, were unmistakable. By 1925 Welch knew for certain that diphtheria had come to Nome.
In desperation, Welch tried treating an infected seven-year-old girl with some expired antitoxin – but she died just a few hours after he administered it.
AN INACCESSIBLE CURE
A vaccine for diphtheria wouldn’t be widely available until the mid-1930s and early 1940s – so an outbreak of the disease meant that each of the 10,000 inhabitants of Nome were all at serious risk.
One option was to use something called an antitoxin – a serum consisting of anti-diphtheria antibodies – to treat the patients. However, the town’s reserve of diphtheria antitoxin had expired. Welch had ordered a replacement shipment of antitoxin the previous summer – but the shipping port that was set to deliver the serum had been closed due to ice, and no new antitoxin would arrive before spring of 1925. In desperation, Welch tried treating an infected seven-year-old girl with some expired antitoxin – but she died just a few hours after he administered it.
Welch radioed for help to all the major towns in Alaska as well as the US Public Health Service in Washington, DC. His telegram read: An outbreak of diphtheria is almost inevitable here. I am in urgent need of one million units of diphtheria antitoxin. Mail is the only form of transportation.
FOUR-LEGGED HEROES
When the Alaskan Board of Health learned about the outbreak, the men rushed to devise a plan to get antitoxin to Nome. Dropping the serum in by airplane was impossible, as the available planes were unsuitable for flying during Alaska’s severe winter weather, where temperatures were routinely as cold as -50 degrees Fahrenheit.
In late January 1925, roughly 30,000 units of antitoxin were located in an Anchorage hospital and immediately delivered by train to a nearby city, Nenana, en route to Nome. Nenana was the furthest city that was reachable by rail – but unfortunately it was still more than 600 miles outside of Nome, with no transportation to make the delivery. Meanwhile, Welch had confirmed 20 total cases of diphtheria, with dozens more at high risk. Diphtheria was known for wiping out entire communities, and the entire town of Nome was in danger of suffering the same fate.
It was Mark Summer, the Board of Health superintendent, who suggested something unorthodox: Using a relay team of sled-racing dogs to deliver the antitoxin serum from Nenana to Nome. The Board quickly voted to accept Summer’s idea and set up a plan: The thousands of units of antitoxin serum would be passed along from team to team at different towns along the mail route from Nenana to Nome. When it reached a town called Nulato, a famed dogsled racer named Leonhard Seppala and his experienced team of huskies would take the serum more than 90 miles over the ice of Norton Sound, the longest and most treacherous part of the journey. Past the sound, the serum would change hands several times more before arriving in Nome.
Between January 27 and 31, the serum passed through roughly a dozen drivers and their dog sled teams, each of them carrying the serum between 20 and 50 miles to the next destination. Though each leg of the trip took less than a day, the sub-zero temperatures – sometimes as low as -85 degrees – meant that every driver and dog risked their lives. When the first driver, Bill Shannon, arrived at his checkpoint in Tolovana on January 28th, his nose was black with frostbite, and three of his dogs had died. The driver who relieved Bill Shannon, named Edgar Kalland, needed the owner of a local roadhouse to pour hot water over his hands to free them from the sled’s metal handlebar. Two more dogs from another relay team died before the serum was passed to Seppala at a town called Ungalik.
THE FINAL STRETCHES
Seppala and his team raced across the ice of the Norton Sound in the dead of night on January 31, with wind chill temperatures nearing an astonishing -90 degrees. The team traveled 84 miles in a single day before stopping to rest – and once rested, they set off again in the middle of the night through a raging winter storm. The team made it across the ice, as well as a 5,000-foot ascent up Little McKinley Mountain, to pass the serum to another driver in record time. The serum was now just 78 miles from Nome, and the death toll in town had reached 28.
The serum reached Gunnar Kaasen and his team of dogs on February 1st. Balto, Kaasen’s lead dog, guided the team heroically through a winter storm that was so severe Kaasen later reported not being able to see the dogs that were just a few feet ahead of him.
Visibility was so poor, in fact, that Kaasen ran his sled two miles past the relay point before noticing – and not wanting to lose a minute, he decided to forge on ahead rather than doubling back to deliver the serum to another driver. As they continued through the storm, the hurricane-force winds ripped past Kaasen’s sled at one point and toppled the sled – and the serum – overboard. The cylinder containing the antitoxin was left buried in the snow – and Kaasen tore off his gloves and dug through the tundra to locate it. Though it resulted in a bad case of frostbite, Kaasen eventually found the cylinder and kept driving.
Kaasen arrived at the next relay point on February 2nd, hours ahead of schedule. When he got there, however, he found the relay driver of the next team asleep. Kaasen took a risk and decided not to wake him, fearing that time would be wasted with the next driver readying his team. Kaasen, Balto, and the rest of the team forged on, driving another 25 miles before finally reaching Nome just before six in the morning. Eyewitnesses described Kaasen pulling up to the town’s bank and stumbling to the front of the sled. There, he collapsed in exhaustion, telling onlookers that Balto was “a damn fine dog.”
A LIVING LEGACY
Just a few hours after Balto’s heroic arrival in Nome, the serum had been thawed and was ready to administer to the patients with diphtheria. Amazingly, the relay team managed to complete the entire journey in just 127 hours – a world record at the time – without one serum vial damaged or destroyed. The serum shipment that arrived by dogsled – along with additional serum deliveries that followed in the next several weeks – were successful in stopping the outbreak in its tracks.
Balto and several other dogs – including Togo, the lead dog on Seppala’s team – were celebrated as local heroes after the race. Balto died in 1933, while the last of the human serum runners died in 1999 – but their legacy lives on: In early 2021, an all-female team of healthcare workers made the news by braving the Alaskan winter to deliver COVID-19 vaccines to people in rural North Alaska, traveling by bobsled and snowmobile – a heroic journey, and one that would have been unthinkable had Balto, Togo, and the 1925 sled runners not first paved the way.