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.
In Ethiopia, Samuna’s three donkeys help her transport produce to market and to collect the water essential to her family, neighbours and livestock. Donkeys are more endangered than people realize, experts say.
“That's the reason why some breeds begin to disappear because humans were not really interested in having that specific breed anymore,” Gambini says. Nonetheless, in Africa, India and Latin America millions of rural families still rely on these hardy creatures for agriculture and transportation. And the only two wild donkey species—Equus africanus in Africa and Equus hemionus in Asia—are also dwindling, due to losing their habitats to human activities, diseases and slow reproduction rates. Gambini’s team wanted to create a way to preserve the animals for the future. “Donkeys are more endangered than people realize,” he says.
There’s much more to donkeys' trouble though. For the past 20 or so years, they have been facing a huge existential threat due to their hide gelatin, a compound derived from their skins by soaking and stewing. In Chinese traditional medicine, the compound, called ejiao, is believed to have a medicinal value, so it’s used in skin creams, added to food and taken in capsules. Centuries ago, ejiao was a very expensive luxury product available only for the emperor and his household. That changed in the 1990s when the Chinese economy boomed, and many people were suddenly able to afford it. “It went from a very elite product to a very popular product,” says Janneke Merkx, a campaign manager at The Donkey Sanctuary, a United Kingdom-based nonprofit organization that keeps tabs on the animals’ welfare worldwide. “It is a status symbol for gift giving.”
Having evolved in the harsh and arid mountainous terrains where food and water were scarce, donkeys are extremely adaptable and hardy. But the Donkey Sanctuary documented cases in which an entire village had their animals disappear overnight, finding them killed and skinned outside their settlement.
The Chinese donkey population was quickly decimated. Unlike many other farm animals, donkeys are finicky breeders. When stressed and unhappy, they don’t procreate, so growing them in large industrial settings isn’t possible. “Donkeys are notoriously slow breeders and really very difficult to farm,” says Merkx. “They are not the same as other livestock like sheep and pigs and cattle.” Within years the, the donkey numbers in China dropped precipitously. “China used to have the largest donkey population in the world in the 1990s. They had 11 million donkeys, and it's now down to less than 3 million, and they just can't keep up with the demand.”
To keep the ejiao conveyor going, some producers turned to the illegal wildlife trade. Poachers began to steal and slaughter donkeys from rural villages in Africa. The Donkey Sanctuary documented cases in which an entire village had their animals disappear overnight, finding them killed and skinned outside their settlement. Exactly how many creatures were lost to the skin trade to-date isn’t possible to calculate, says Faith Burden, the Donkey Sanctuary’s director of equine operations. Traditionally a poor people’s beast of burden, donkey counts are hard to keep track of. “When an animal doesn't produce meat, milk or eggs or whatever edible product, they're often less likely to be acknowledged in a government population census,” Burden says. “So reliable statistics are hard to come by.” The nonprofit estimates that about 4.8 million are slaughtered annually.
During their six to seven thousand years of domestication, donkeys rarely got the full appreciation for their services. They are often compared to horses, which doesn’t do them justice. They’re entirely different animals, Burden says. Built for speed, horses respond to predators and other dangers by running as fast as they can. Donkeys, which originate from the rocky, mountainous regions of Africa where running is dangerous, react to threats by freezing and assessing the situation for the best response. “Those so-called stubborn donkeys that won’t move as you want, they are actually thinking ‘what’s the best approach,’” Burden says. They may even choose to fight the predators rather than flee, she adds. “In some parts of the world, people use them as guard animals against things like coyotes and wolves.”
Scientists believe that domestic donkeys take their origin from Equus africanus or African wild ass, originally roaming where Kenya, Ethiopia and Eritrea are today. Having evolved in the harsh and arid mountainous terrains where food and water were scarce, they are extremely adaptable and hardy. Research finds that they can go without water for 72 hours and then drink their fill without any negative consequences. Their big jaws let them chew tough desert shrubs, which horses can’t exist on. Their large ears help dissipate heat. Their little upright hooves are a perfect fit for the uneven rocky or other dangerous grounds. Accustomed to the mountain desert climate with hot days and cold nights, they don’t mind temperature flux.
“The donkey is the most supremely adapted animal to deal with hostile conditions,” Burden says. “They can survive on much lower nutritional quality food than a cow, sheep or horse. That’s why communities living in some of the most inhospitable places will often have donkeys with them.” And that’s why losing a donkey to an illegal skin trade can devastate a family in places like Eritrea. Suddenly everything from water to firewood to produce must be carried by family members—and often women.
Workers unloading donkeys at the Shinyanga slaughterhouse in Tanzania. Fearing a future in which donkeys go extinct, scientists have found ways to cryopreserve a donkey embryo in liquid nitrogen.
TAHUCHA
One can imagine a time when worldwide donkey populations may dwindle to the point that they would need to be restored. That includes their genetic variability too. That’s where the frozen embryos may come in handy. We may be able to use them to increase the genetic variability of donkeys, which will be especially important if they get closer to extinction, Gambini says. His team had already created frozen embryos for horses and zebras, an idea similar to a seed bank. “We call this concept the Frozen Zoo.”
Creating donkey embryos proved much harder than those of zebras and horses. To improve chances of fertilization, Gambini used the intracytoplasmic sperm injection or ICSI, in which he employed a tiny needle called a micropipette to inject a donkey sperm into an egg. That was a step above the traditional IVF method, in which the egg and a sperm are left floating in a test tube together. The injection took, but during the incubating week, one after the other, the embryos stopped dividing. Finally, on day seven, Gambini finally spotted the exact sight he was hoping to see. One of the embryos developed into a burgeoning ball of cells.
“That stage is called a blastocyst,” Gambini says. The clump of cells had a lot of fluids mixed within them, which indicated that they were finally developing into a viable embryo. “When we see a blastocyst, we know we can transfer that into a female.” He was so excited he immediately called all his collaborators to tell them the good news, which they later published in the journal of Theriogenology.
The one and only embryo to reach that stage, the blastocyst was cryopreserved in liquid nitrogen. The team is waiting for the next breeding season to see if a female donkey may carry it to term and give birth to a healthy foal. Gambini’s team is hoping to polish the process and create more embryos. “It’s our weapon in the conservation ass-enal,” he says.
