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.
A bioengineer at the University of California, Riverside, may have found a way to prevent counterfeit medications: pill coatings inspired by the sprinkles on baked goods and candies.
The idea was borne out of pandemic boredom. Confined to his home, Grover was struck by the patterns of nonpareils he saw on candies, and found himself counting the number of little balls on each one. “It’s random, how they’re applied,” he says. “I wondered if it ever repeats itself or if each of these candies is unique in the entire world.” He suspected the latter, and some quick math proved his hypothesis: Given dozens of nonpareils per candy in a handful of different colors, it’s highly unlikely that the sprinklings on any two candies would be identical.
He quickly realized his finding could have practical applications: pills or capsules could be coated with similar “sprinkles,” with the manufacturer photographing each pill or capsule before selling its products. Consumers looking to weed out fakes could potentially take a photo with their cell phones and go online to compare images of their own pills to the manufacturer’s database, with the help of an algorithm that would determine their authenticity. Or, a computer could generate another type of unique identifier, such as a text-based code, tracking to the color and location of the sprinkles. This would allow for a speedier validation than a photo-based comparison, Grover says. “It could be done very quickly, in a fraction of a second.”
Researchers and manufacturers have already developed some anti-counterfeit tools, including built-in identifiers like edible papers with scannable QR codes. But such methods, while functional, can be costly to implement, Grover says.
It wouldn’t be paranoid to take such precautions. Counterfeits are a growing problem, according to Young Kim, a biomedical engineer at Purdue University who was not involved in the CandyCodes study. “There are approximately 40,000 online pharmacies that one can access via the Internet,” he says. “Only three to four percent of them are operated legally.” Purchases from online pharmacies rose dramatically during the pandemic, and Kim expects a boom in counterfeit medical products alongside it.
The FDA warns that U.S. consumers can be exposed to counterfeits through online purchases, in particular. The problem is magnified in low- to middle-income nations, where one in 10 medical products are counterfeit, according to a World Health Organization estimate. Cost doesn’t seem to be a factor, either; antimalarials and antibiotics are most often reported as counterfeits or fakes, and generic medications are swapped as often as brand-name drugs, according to the same WHO report.
Counterfeits weren’t tracked globally until 2013; since then, there have been 1,500 reports to the WHO, with actual incidences of counterfeiting likely much higher. Fake medicines have been estimated to result in costs of $200 billion each year, and are blamed for more than 72,000 pneumonia- and 116,000 malaria-related deaths.
Researchers and manufacturers have already developed some anti-counterfeit tools, including built-in identifiers like edible papers with scannable QR codes or barcodes that are stamped onto or otherwise incorporated into pills and other medical products. But such methods, while functional, can be costly to implement, Grover says.
CandyCodes could provide unique identifiers for at least 41 million pills for every person on the planet.
William Grover
“Putting universal codes on each pill and each dosage is attractive,” he says. “The challenge is, how can we do it in a way that requires as little modification to the existing manufacturing process as possible? That's where I hope CandyCodes have an edge. It's not zero modification, but I hope it is as minor a modification of the manufacturing process as possible.”
Kim calls the concept “a clever idea to introduce entropy for high-level security” even if it may not be as close to market as other emerging technologies, including some edible watermarks he’s helped develop. He points out that CandyCodes still needs to be tested for reproducibility and readability.
The possibilities are already intriguing, though. Grover’s recent research, published in Scientific Reports, predicts that unique codes could be used for at least 41 million pills for every person on the planet.
Sadly, CandyCodes’ multicolored bits probably won’t taste like candy. They must be made of non-caloric ingredients to meet the international regulatory standards that govern food dyes and colorants. But Grover hopes CandyCodes represent a simple, accessible solution to a heart-wrenching issue. “This feels like trying to track down and go after bad guys,” he says. “Someone who would pass off a medicine intended for a child or a sick person and pass it off as something effective, I can't imagine anything much more evil than that. It's fun and, and a little fulfilling to try to develop technologies that chip away at that.”
In 2015, human poop was valued at $9.5 billion per year, which today would be $11.5 billion. The Ocean Sewage Alliance is uniting experts from key sectors to change how we handle our sewage and, in the process, create all sorts of economic benefits.
Most of us don’t think much about what happens after we flush the toilet. Most of us probably assume that the substances we flush go “somewhere” and are dealt with safely. But we typically don’t think about it beyond that.
Most of us also probably don’t think about what’s in the ocean or lakes we swim in. Since others are swimming, jumping in is just fine. But our waterways are far from clean. In fact, at times they are incredibly filthy. In the US, we are dumping 1.2 trillion of gallons of untreated sewage into the environment every year. Just New York City alone discharges 27 billion gallons into the Hudson River basin annually.
How does this happen? Part of it is the unfortunate side effect of our sewage system design that dates back to over a century ago when cities were smaller and fewer people were living so close together.
Back then, engineers designed the so-called “combine sewer overflow systems,” or CSOs, in which the storm water pipes are connected to the sanitary sewer pipes. In normal conditions, the sewage effluent from homes flows to the treatment plants where it gets cleaned and released into the waterways. But when it rains, the pipe system becomes so overwhelmed with water that the treatment plant can’t process it fast enough. So the treatment plant has to release the excess water through its discharge pipes—directly, without treatment, into streams, rivers and the ocean.
The 1.2 trillion gallons of CSO releases isn’t even the full picture. There are also discharges from poorly maintained septic systems, cesspools and busted pipes of the aging wastewater infrastructure. The state of Hawaii alone has 88,000 cesspools that need replacing and are currently leaking 53 million gallons of raw sewage daily into their coastal waters. You may think twice about swimming on your Hawaii vacations.
Overall, the US is facing a $271 billion backlog in wastewater infrastructure projects to update these aging systems. Across the Western world, countries are facing similar challenges with their aging sewage systems, especially the UK and European Union.
That’s not to say that other parts of the planet are in better shape. Out of the 7+ billion people populating our earth, 4.2 billion don’t have access to safe sanitation. Included in this insane number are roughly 2 billion people who have no toilet at all. Whether washed by rains or dumped directly into the waterways, a lot of this sludge pollutes the environment, the drinking water, and ultimately the ocean.
Pipes pour water onto a rocky shore in Jakarta, Indonesia.
Tom Fisk
What complicates this from an ocean health perspective is that it’s not just poop and pee that gets dumped into nearby waterways. It is all the things we put in and on our bodies and flush down our drains. That vicious mix of chemicals includes caffeine, antibiotics, antidepressants, painkillers, hormones, microplastics, cocaine, cooking oils, paint thinners, and PFAS—the forever chemicals present in everything from breathable clothing to fire retardant fabrics of our living room couches. Recent reports have found all of the above substances in fish—and then some.
Why do we allow so much untreated sewage spill into the sea? Frankly speaking, for decades scientists and engineers thought that the ocean could handle it. The mantra back then was “dilution is the solution to pollution,” which might’ve worked when there were much fewer people living on earth—but not now. Today science is telling us that this old approach doesn’t hold. That marine habitats are much more sensitive than we had expected and can’t handle the amount of wastewater we are discharging into them.
The excess nitrogen and phosphorus that the sewage (and agricultural runoff) dumps into the water causes harmful algal blooms, more commonly known as red or brown tides. The water column is overtaken by tiny algae that sucks up all the oxygen from the water, creating dead zones like the big fish kills in the Gulf of Mexico. These algae also cause public health issues by releasing gases toxic to people and animals, including dementia, neurological damage, and respiratory illness. Marshes and mangroves end up with weakened root systems and start dying off. In a wastewater modeling study I published last year, we found that 31 percent of salt marshes globally were heavily polluted with human sewage. Coral reefs get riddled with disease and overgrown by seaweed.
We could convert sewage into high-value goods. It can be used to generate electricity, fertilizer, and drinking water. The technologies not only exist but are getting better and more efficient all the time.
Moreover, by way of our sewage, we managed to transmit a human pathogen—Serratia marcescens, which causes urinary, respiratory and other infections in people—to corals! Recent reports from the Florida Keys are showing white pox disease popping up in elk horn corals caused by S.marcescens, which somehow managed to jump species. Many recent studies have documented just how common this type of pollution is across the globe.
Yet, there is some good news in that abysmal sewage flow. Just like with plastic pollution, realizing that there’s a problem is the first step, so awareness is key. That’s exactly why I co-founded Ocean Sewage Alliance last year—a nonprofit that aims to “re-potty train the world” by breaking taboos in talking about the poop and pee problem, as well as uniting experts from various key sectors to work together to end sewage pollution in coastal areas.
To end this pollution, we have to change the ways we handle our sewage. Even more exciting is that by solving the sewage problem we can create all sorts of economic benefits. In 2015, human poop was valued at $9.5 billion a year globally, which today would be $11.5 billion per year.
What would one do with that sh$t?
We could convert it into high-value goods. Sewage can be used to generate electricity, fertilizer, and drinking water. The technologies not only exist but are getting better and more efficient all the time. Some exciting examples include biodigesters and urine diversion (or peecycling) systems that can produce fertilizer and biogas, essentially natural gas. The United Nations estimates that the biogas produced from poop could provide electricity for 138 million homes. And the recovered and cleaned water can be used for irrigation, laundry and flushing toilets. It can even be refined to the point that it is safe for drinking water – just ask the folks in Orange County, CA who have been doing so for the last few decades.
How do we deal with all the human-made pollutants in our sewage? There is technology for that too. Called pyrolysis, it heats up sludge to high temperatures in the absence of oxygen, which causes most of the substances to degrade and fall apart.
There are solutions to the problems—as long as we acknowledge that the problems exist. The fact that you are reading this means that you are part of the solution already. The next time you flush your toilet, think about where this output may flow. Does your septic system work properly? Does your local treatment plant discharge raw sewage on rainy days? Can that plant implement newer technologies that can upcycle waste? These questions are part of re-potty training the world, one household at a time. And together, these households are the force that can turn back the toxic sewage tide. And keep our oceans blue.