Scientists Are Building an “AccuWeather” for Germs to Predict Your Risk of Getting the Flu
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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.
Podcast: Trusting Science with Dr. Sudip Parikh, CEO of AAAS
The "Making Sense of Science" podcast features interviews with leading experts about health innovations and the big ethical and social questions they raise. The podcast is hosted by Matt Fuchs, editor of the award-winning science outlet Leaps.org.
As Pew research showed last month, many Americans have less confidence in science these days - our collective trust has declined to levels below when the pandemic began. But leaders like Dr. Sudip Parikh are taking important steps to more fully engage people in scientific progress, including breakthroughs that could benefit health and prevent disease. In January 2020, Sudip became the 19th Chief Executive Officer of the American Association for the Advancement of Science (AAAS), an international nonprofit that seeks to advance science, engineering and innovation throughout the world, with 120,000 members in 91 countries. He is the executive publisher of Science, one of the top academic journals in the world, and the Science family of journals.
Listen to the episode
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In this episode, Sudip and I talk about:
- Reasons to be excited about health innovations that could come to fruition in the next several years.
- Sudip's thoughts about areas of health innovation where we should be especially cautious.
- Strategies for scientists and journalists to instill greater trust in science.
- How to tap into and nurture kids' passion for STEM subjects.
- The best roles for experts to play in society and the challenges they face.
And we pack several other fascinating topics into our 35 minutes. Here are links to check out and learn more about Sudip Parikh and AAAS:
- Sudip Parikh's official bio - https://www.aaas.org/person/sudip-parikh
- Sudip Parikh, Why We Must Rebuild Trust in Science, Trend Magazine, Feb. 9, 2021 - https://www.pewtrusts.org/en/trend/archive/winter-...
- Follow Sudip on Twitter - https://twitter.com/sudipsparikh
- AAAS website - https://www.aaas.org/
- AAAS podcast - https://www.science.org/podcasts
- The latest issue of Science - https://www.science.org/
- Science Journals homepage - https://www.science.org/journals
- AAAS Mentor Resources - https://www.aaas.org/stemmentoring
- AAAS Science Journalism Awards - https://sjawards.aaas.org/enter
- Pew Research Center Report, Americans' Trust in Scientists, Other Groups Declines, Feb. 15, 2022 https://www.pewresearch.org/science/2022/02/15/ame...
An implant, combined with the glasses and tiny video camera modeled in this photo, could improve the eyesight of millions of people with degenerative eye diseases in the coming years.
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.”