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.
Did researchers finally find a way to lick COVID?
Already vaccinated and want more protection from COVID-19? A protein found in ice cream could help, some research suggests, though there are a bunch of caveats.
The protein, called lactoferrin, is found in the milk of mammals and thus in dairy products, including ice cream. It has astounding antiviral properties that have been taken for granted and remain largely unexplored because it is a natural product, meaning that it cannot be patented and exploited by pharmaceutical companies.
Still, a few researchers in Europe and elsewhere have sought to better understand the compound.
Jonathan Sexton runs a drug screening program at the University of Michigan where cells are infected with a pathogen and then exposed to a library of the thousands of small molecule drug compounds – which can enter the body more easily than drugs with heavier molecules – approved by the FDA. In addition, the library includes compounds that passed phase 1 safety studies but later proved ineffective against the targeted disease. Each drug is dissolved in a solvent for exposure to the cells in the laborious testing process made feasible by robotic automation.
When COVID hit, researchers scrambled to identify any approved drug that might help fight the infection. Sexton decided to screen the drug library as well as some dietary supplements against SARS-CoV-2, the virus that causes the disease. Sexton says that the grunt work fell to Jesse Wotring, “a very talented PhD student,” who pulled lactoferrin off the shelf. But the regular solvent used in the testing process would destroy the protein, so he had to take another approach and do all the work by hand.
“We were agnostic,” says Sexton, who didn't have a strong interest in lactoferrin or any of the other compounds in the library, but the data was quite clear; lactoferrin “consistently produced the best efficacy...it was the absolute home run.” The findings were published in separate papers last year and in February.
It turns out that lactoferrin has several different mechanisms of action against SARS-CoV-2, inhibiting the virus from entering cells, moving around within them and replicating. Lactoferrin also modulates the overall immune response, which makes it difficult for the virus to simultaneously mutate resistance to the protein at every step of replication. “It has broad efficacy against every [SARS-CoV-2] variant that we've tested,” he says.
From bench to bedside
Sexton's initial interest was to develop a drug for the acute phase of COVID infection, to treat a hospitalized patient or prevent that hospitalization. But with the quick approval of vaccines and drugs to treat the disease, he increasingly focused on ways to better prevent infection and inhibit spread of the virus.
“If you can get lactoferrin to persist in your upper GI tract, then it may very well prevent the primary infection, and that's what we're really interested in.” He reasoned that a chewing gum formula might release enough lactoferrin into the mucosal tissue of the mouth and upper airways to inhibit replication and give the immune system a chance to knock out the virus before it can establish a foothold. It could also reduce the amount of virus spread through talking.
To get enough lactoferrin to have a possible beneficial effect, one would have to drink gallons of milk a day, “and that would have other undesirable consequences, like getting extremely obese,” says Sexton. Obesity is one of the leading risk factors for severe COVID disease.
Testing that theory has been difficult. The easiest way would be a “challenge trial,” where volunteers take the drug, or in this case gum, are exposed to the pathogen, and protection is measured. Some COVID challenge studies have been conducted in Europe but the FDA remains hesitant to allow such a study in the U.S. A traditional prevention study would be like a vaccine trial, involving thousands, perhaps tens of thousands of volunteers over a period of months or years, and it would be very expensive. No one has stepped forward to foot the bill.
So the next step for Sexton is a clinical trial of newly diagnosed COVID patients who will be given standard of care treatment, and layered on top of that they will receive either lactoferrin, probably in pill form, or a placebo. He has identified initial funding. “We would study their viral load over time as well as their symptoms.”
One issue the FDA is grappling with in considering the proposed trial is that it typically decides whether to approve drugs from a factory by applying a rigorous standard, called good manufacturing practices, while food products, which are the source of lactoferrin, are produced under somewhat different standards. The agency still has not finalized rules on how to deal with natural products used as drugs, such as fecal transplants, convalescent plasma, or medical marijuana.
Sexton is frustrated by the delay because lactoferrin derived from bovine milk whey has been used for many decades as a protein supplement by athletes, it is a large component of most infant formula, and the largest number of clinical studies of lactoferrin involve premature infants. There is no question of its safety, he says.
Do it yourself
So what can you do while waiting for regulatory wheels to spin and clinical trial data to be generated?
Could a dose of Ben & Jerry's provide some protection against SARS-CoV-2?
Sexton chuckles at the suggestion. He supposes it couldn't hurt. But to get enough lactoferrin to have a possible beneficial effect, one would have to drink gallons of milk a day, “and that would have other undesirable consequences, like getting extremely obese.” Obesity is one of the leading risk factors for severe COVID disease.
Pseudo-milk products made from soy, almonds, oats, or other plant products do not contain lactoferrin; it has to come from a teat. So that rules them out.
Whey-based protein shakes might be a useful way to add lactoferrin to the diet.
Probably the best option is to take conventional gelatin capsules of lactoferrin that are widely available wherever supplements are sold. Sexton calculates that about a gram a day, four 250 milligram capsules, should do it. He advises two in the morning and two a night. “You really want to take them on an empty stomach...your stomach treats [the lactoferrin protein] like it would a steak” and chops it for absorption in the intestine, which you do not want. About 70 percent of lactoferrin can get through an empty stomach, but eating food cranks up digestive gastric acids and the amount of intact lactoferrin that gets through to the gut plummets.
Sexton cautions, “We have not determined clinical efficacy yet,” and he is not offering advice as a physician, but in the spirit of harm reduction, he realizes that some people are going to try things that might help them. Lactoferrin “is remarkably safe. And so people have to make their own decisions about what they are willing to take and what they are not,” he says.
My guest today for the Making Sense of Science podcast is Camila dos Santos, associate professor at Cold Spring Harbor Lab, who is a leading researcher of the inner lives of human mammary glands, more commonly known as breasts. These organs are unlike any other because throughout life they undergo numerous changes, first in puberty, then during pregnancies and lactation periods, and finally at the end of the cycle, when babies are weaned. A complex interplay of hormones governs these processes, in some cases increasing the risk of breast cancer and sometimes lowering it. Witnessing the molecular mechanics behind these processes in humans is not possible, so instead Dos Santos studies organoids—the clumps of breast cells donated by patients who undergo breast reduction surgeries or biopsies.
Show notes:
2:52 In response to hormones that arise during puberty, the breast cells grow and become more specialized, preparing the tissue for making milk.
7:53 How do breast cells know when to produce milk? It’s all governed by chemical messaging in the body. When the baby is born, the brain will release the hormone called oxytocin, which will make the breast cells contract and release the milk.
12:40 Breast resident immune cells are including T-cells and B-cells, but because they live inside the breast tissue their functions differ from the immune cells in other parts of the body,
17:00 With organoids—dimensional clumps of cells that are cultured in a dish—it is possible to visualize and study how these cells produce milk.
21:50 Women who are pregnant later in life are more likely to require medical intervention to breastfeed. Scientists are trying to understand the fundamental reasons why it happens.
26:10 Breast cancer has many risks factors. Generic mutations play a big role. All of us have the BRCA genes, but it is the alternation in the DNA sequence of the BRCA gene that can increase the predisposition to breast cancer. Aging and menopause are the risk factors for breast cancer, and so are pregnancies.
29:22 Women that are pregnant before the age of 20 to 25, have a decreased risk of breast cancer. And the hypothesis here is that during pregnancy breast cells more specialized, as specialized cells, they have a limited lifespan. It's more likely that they die before they turn into cancer.
33:08 Organoids are giving scientists an opportunity to practice personalized medicine. Scientists can test drugs on organoids taken from a patient to identify the most efficient treatment protocol.
Links:
Camila dos Santos’s Lab Page.
Editor's note: In addition to being a regular writer for Leaps.org, Lina Zeldovich is the guest host for today's episode of the Making Sense of Science podcast.
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.