An At-Home Contagiousness Test for COVID-19 Already Exists. Why Can’t We Use It?
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
You're lying in bed late at night, the foggy swirl of the pandemic's 8th month just beginning to fall behind you, when you detect a slight tickle at the back of your throat.
"If half of people choose to use these tests every other day, then we can stop transmission faster than a vaccine can."
Suddenly fully awake, a jolt of panicked electricity races through your body. Has COVID-19 come for you? In the U.S., answering this simple question is incredibly difficult.
Now, you might have to wait for hours in line in your car to get a test for $100, only to find out your result 10-14 days later -- much too late to matter in stopping an outbreak. Due to such obstacles, a recent report in JAMA Internal Medicine estimated that 9 out of 10 infections in the U.S. are being missed.
But what if you could use a paper strip in the privacy of your own home, like a pregnancy test, and find out if you are contagious in real time?
e25 Bio, a small company in Cambridge, Mass., has already created such a test and it has been sitting on a lab bench, inaccessible, since April. It is an antigen test, which looks for proteins on the outside of a virus, and can deliver results in about 15 minutes. Also like an over-the-counter pregnancy test, e25 envisions its paper strips as a public health screening tool, rather than a definitive diagnostic test. People who see a positive result would be encouraged to then seek out a physician-administered, gold-standard diagnostic test: the more sensitive PCR.
Typically, hospitals and other health facilities rely on PCR tests to diagnose viruses. This test can detect small traces of genetic material that a virus leaves behind in the human body, which tells a clinician that the patient is either actively infected with or recently cleared that virus. PCR is quite sensitive, meaning that it is able to detect the presence of a virus' genetic material very accurately.
But although PCR is the gold-standard for diagnostics, it's also the most labor-intensive way to test for a virus and takes a relatively long time to produce results. That's not a good match for stopping super-spreader events during an unchecked pandemic. PCR is also not great at identifying the infected people when they are most at risk of potentially transmitting the virus to others.
That's because the viral threshold at which PCR can detect a positive result is so low, that it's actually too sensitive for the purposes of telling whether someone is contagious.
"The majority of time someone is PCR positive, those [genetic] remnants do not indicate transmissible virus," epidemiologist Michael Mina recently Tweeted. "They indicate remnants of a recently cleared infection."
To stop the chain of transmission for COVID-19, he says, "We need a more accurate test than PCR, that turns positive when someone is able to transmit."
In other words, we need a test that is better at detecting whether a person is contagious, as opposed to whether a small amount of virus can be detected in their nose or saliva. This kind of test is especially critical given the research showing that asymptomatic and pre-symptomatic people have high viral loads and are spreading the virus undetected.
The critical question for contagiousness testing, then, is how big a dose of SARS-CoV-2, the virus that causes COVID, does it take to infect most people? Researchers are still actively trying to answer this. As Angela Rasmussen, a coronavirus expert at Columbia University, told STAT: "We don't know the amount that is required to cause an infection, but it seems that it's probably not a really, really small amount, like measles."
Amesh Adalja, an infectious disease physician and a senior scholar at the Johns Hopkins University Center for Health Security, told LeapsMag: "It's still unclear what viral load is associated with contagiousness but it is biologically plausible that higher viral loads, in general, are associated with more efficient transmission especially in symptomatic individuals. In those without symptoms, however, the same relationship may not hold and this may be one of the reasons young children, despite their high viral loads, are not driving outbreaks."
"Antigen tests work best when there's high viral loads. They're catching people who are super spreaders."
Mina and colleagues estimate that widespread use of weekly cheap, rapid tests that are 100 times less sensitive than PCR tests would prevent outbreaks -- as long as the people who are positive self-isolate.
So why can't we buy e25Bio's test at a drugstore right now? Ironically, it's barred for the very reason that it's useful in the first place: Because it is not sensitive enough to satisfy the U.S. Food and Drug Administration, according to the company.
"We're ready to go," says Carlos-Henri Ferré, senior associate of operations and communications at e25. "We've applied to FDA, and now it's in their hands."
The problem, he said, is that the FDA is evaluating applications for antigen tests based on criteria for assessing diagnostics, like PCR, even when the tests serve a different purpose -- as a screening tool.
"Antigen tests work best when there's high viral loads," Ferré says. "They're catching people who are super spreaders, that are capable of continuing the spread of disease … FDA criteria is for diagnostics and not this."
FDA released guidance on July 29th -- 140 days into the pandemic -- recommending that at-home tests should perform with at least 80 percent sensitivity if ordered by prescription, and at least 90 percent sensitivity if purchased over the counter. "The danger of a false negative result is that it can contribute to the spread of COVID-19," according to an FDA spokesperson. "However, oversight of a health care professional who reviews the results, in combination with the patient's symptoms and uses their clinical judgment to recommend additional testing, if needed, among other things, can help mitigate some risks."
Crucially, the 90 percent sensitivity recommendation is judged upon comparison to PCR tests, meaning that if a PCR test is able to detect virus in 100 samples, the at-home antigen test would need to detect virus in at least 90 of those samples. Since antigen tests only detect high viral loads, frustrated critics like Mina say that such guidance is "unreasonable."
"The FDA at this moment is not understanding the true potential for wide-scale frequent testing. In some ways this is not their fault," Mina told LeapsMag. "The FDA does not have any remit to evaluate tests that fall outside of medical diagnostic testing. The proposal I have put forth is not about diagnostic testing (leave that for symptomatic cases reporting to their physician and getting PCR tests)....Daily rapid tests are not about diagnosing people and they are not about public health surveillance and they are not about passports to go to school, out to dinner or into the office. They are about reducing population-level transmission given a similar approach as vaccines."
A reasonable standard, he added, would be to follow the World Health Organization's Target Product Profiles, which are documents to help developers build desirable and minimally acceptable testing products. "A decent limit," Mina says, "is a 70% or 80% sensitivity (if they truly require sensitivity as a metric) to detect virus at Ct values less than 25. This coincides with detection of the most transmissible people, which is important."
(A Ct value is a type of measurement that corresponds inversely to the amount of viral load in a given sample. Researchers have found that Ct values of 13-17 indicate high viral load, whereas Ct values greater than 34 indicate a lack of infectious virus.)
"We believe this should be an at-home test, but [if FDA approval comes through] the first rollout is to do this in laboratories, hospitals, and clinics."
"We believe that population screening devices have an immediate place and use in helping beat the virus," says Ferré. "You can have a significant impact even with a test at 60% sensitivity if you are testing frequently."
When presented with criticism of its recommendations, the FDA indicated that it will not automatically deny any at-home test that fails to meet the 90 percent sensitivity guidance.
"FDA is always open to alternative proposals from developers, including strategies for serial testing with less sensitive tests," a spokesperson wrote in a statement. "For example, it is possible that overall sensitivity of the strategy could be considered cumulatively rather than based on one-time testing….In the case of a manufacturer with an at-home test that can only detect people with COVID-19 when they have a high viral load, we encourage them to talk with us so we can better understand their test, how they propose to use it, and the validation data they have collected to support that use."
However, the FDA's actions so far conflict with its stated openness. e25 ended up adding a step to the protocol in order to better meet FDA standards for sensitivity, but that extra step—sending samples to a laboratory for results—will undercut the test's ability to work as an at-home screening tool.
"We believe this should be an at-home test, but [if FDA approval comes through] the first rollout is to do this in laboratories, hospitals, and clinics," Ferré says.
According to the FDA, no test developers have approached them with a request for an emergency use authorization that proposes an alternate testing paradigm, such as serial testing, to mitigate test sensitivity below 80 percent.
From a scientific perspective, antigen tests like e25Bio's are not the only horse in the race for a simple rapid test with potential for at-home use. CRISPR technology has long been touted as fertile ground for diagnostics, and in an eerily prescient interview with LeapsMag in November, CRISPR pioneer Feng Zhang spoke of its potential application as an at-home diagnostic for an infectious disease specifically.
"I think in the long run it will be great to see this for, say, at-home disease testing, for influenza and other sorts of important public health [concerns]," he said in the fall. "To be able to get a readout at home, people can potentially quarantine themselves rather than traveling to a hospital and then carrying the risk of spreading that disease to other people as they get to the clinic."
Zhang's company Sherlock Biosciences is now working on scaled-up manufacturing of a test to detect SARS CoV-2. Mammoth Biosciences, which secured funding from the National Institutes of Health's Rapid Acceleration of Diagnostics program, is also working on a CRISPR diagnostic for SARS CoV-2. Both would check the box for rapid testing, but so far not for at-home testing, as they would also require laboratory infrastructure to provide results.
If any at-home tests can clear the regulatory hurdles, they would also need to be manufactured on a large scale and be cheap enough to entice people to actually use them. In the world of at-home diagnostics, pregnancy tests have become the sole mainstream victor because they're simple to use, small to carry, easy to interpret, and costs about seven or eight dollars at any ubiquitous store, like Target or Walmart. By comparison, the at-home COVID collection tests that don't even offer diagnostics—you send away your sample to an external lab—all cost over $100 to take just one time.
For the time being, the only available diagnostics for COVID require a lab or an expensive dedicated machine to process. This disconnect could prolong the world's worst health crisis in a century.
"Daily rapid tests have enormous potential to sever transmission chains and create herd effects similar to herd immunity," Mina says. "We all recognize that vaccines and infections can result in herd immunity when something around half of people are no longer susceptible.
"The same thing exists with these tests. These are the intervention to stop the virus. If half of people choose to use these tests every other day, then we can stop transmission faster than a vaccine can. The technology exists, the theory and mathematics back it up, the epidemiology is sound. There is no reason we are not approaching this as strongly as we would be approaching vaccines."
--Additional reporting by Julia Sklar
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
One day in recent past, scientists at Columbia University’s Creative Machines Lab set up a robotic arm inside a circle of five streaming video cameras and let the robot watch itself move, turn and twist. For about three hours the robot did exactly that—it looked at itself this way and that, like toddlers exploring themselves in a room full of mirrors. By the time the robot stopped, its internal neural network finished learning the relationship between the robot’s motor actions and the volume it occupied in its environment. In other words, the robot built a spatial self-awareness, just like humans do. “We trained its deep neural network to understand how it moved in space,” says Boyuan Chen, one of the scientists who worked on it.
For decades robots have been doing helpful tasks that are too hard, too dangerous, or physically impossible for humans to carry out themselves. Robots are ultimately superior to humans in complex calculations, following rules to a tee and repeating the same steps perfectly. But even the biggest successes for human-robot collaborations—those in manufacturing and automotive industries—still require separating the two for safety reasons. Hardwired for a limited set of tasks, industrial robots don't have the intelligence to know where their robo-parts are in space, how fast they’re moving and when they can endanger a human.
Over the past decade or so, humans have begun to expect more from robots. Engineers have been building smarter versions that can avoid obstacles, follow voice commands, respond to human speech and make simple decisions. Some of them proved invaluable in many natural and man-made disasters like earthquakes, forest fires, nuclear accidents and chemical spills. These disaster recovery robots helped clean up dangerous chemicals, looked for survivors in crumbled buildings, and ventured into radioactive areas to assess damage.
Now roboticists are going a step further, training their creations to do even better: understand their own image in space and interact with humans like humans do. Today, there are already robot-teachers like KeeKo, robot-pets like Moffin, robot-babysitters like iPal, and robotic companions for the elderly like Pepper.
But even these reasonably intelligent creations still have huge limitations, some scientists think. “There are niche applications for the current generations of robots,” says professor Anthony Zador at Cold Spring Harbor Laboratory—but they are not “generalists” who can do varied tasks all on their own, as they mostly lack the abilities to improvise, make decisions based on a multitude of facts or emotions, and adjust to rapidly changing circumstances. “We don’t have general purpose robots that can interact with the world. We’re ages away from that.”
Robotic spatial self-awareness – the achievement by the team at Columbia – is an important step toward creating more intelligent machines. Hod Lipson, professor of mechanical engineering who runs the Columbia lab, says that future robots will need this ability to assist humans better. Knowing how you look and where in space your parts are, decreases the need for human oversight. It also helps the robot to detect and compensate for damage and keep up with its own wear-and-tear. And it allows robots to realize when something is wrong with them or their parts. “We want our robots to learn and continue to grow their minds and bodies on their own,” Chen says. That’s what Zador wants too—and on a much grander level. “I want a robot who can drive my car, take my dog for a walk and have a conversation with me.”
Columbia scientists have trained a robot to become aware of its own "body," so it can map the right path to touch a ball without running into an obstacle, in this case a square.
Jane Nisselson and Yinuo Qin/ Columbia Engineering
Today’s technological advances are making some of these leaps of progress possible. One of them is the so-called Deep Learning—a method that trains artificial intelligence systems to learn and use information similar to how humans do it. Described as a machine learning method based on neural network architectures with multiple layers of processing units, Deep Learning has been used to successfully teach machines to recognize images, understand speech and even write text.
Trained by Google, one of these language machine learning geniuses, BERT, can finish sentences. Another one called GPT3, designed by San Francisco-based company OpenAI, can write little stories. Yet, both of them still make funny mistakes in their linguistic exercises that even a child wouldn’t. According to a paper published by Stanford’s Center for Research on Foundational Models, BERT seems to not understand the word “not.” When asked to fill in the word after “A robin is a __” it correctly answers “bird.” But try inserting the word “not” into that sentence (“A robin is not a __”) and BERT still completes it the same way. Similarly, in one of its stories, GPT3 wrote that if you mix a spoonful of grape juice into your cranberry juice and drink the concoction, you die. It seems that robots, and artificial intelligence systems in general, are still missing some rudimentary facts of life that humans and animals grasp naturally and effortlessly.
How does one give robots a genome? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create.
It's not exactly the robots’ fault. Compared to humans, and all other organisms that have been around for thousands or millions of years, robots are very new. They are missing out on eons of evolutionary data-building. Animals and humans are born with the ability to do certain things because they are pre-wired in them. Flies know how to fly, fish knows how to swim, cats know how to meow, and babies know how to cry. Yet, flies don’t really learn to fly, fish doesn’t learn to swim, cats don’t learn to meow, and babies don’t learn to cry—they are born able to execute such behaviors because they’re preprogrammed to do so. All that happens thanks to the millions of years of evolutions wired into their respective genomes, which give rise to the brain’s neural networks responsible for these behaviors. Robots are the newbies, missing out on that trove of information, Zador argues.
A neuroscience professor who studies how brain circuitry generates various behaviors, Zador has a different approach to developing the robotic mind. Until their creators figure out a way to imbue the bots with that information, robots will remain quite limited in their abilities. Each model will only be able to do certain things it was programmed to do, but it will never go above and beyond its original code. So Zador argues that we have to start giving robots a genome.
How does one do that? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create. Genomes lay out rules for brain development. Specifically, the genome encodes blueprints for wiring up our nervous system—the details of which neurons are connected, the strength of those connections and other specs that will later hold the information learned throughout life. “Our genomes serve as blueprints for building our nervous system and these blueprints give rise to a human brain, which contains about 100 billion neurons,” Zador says.
If you think what a genome is, he explains, it is essentially a very compact and compressed form of information storage. Conceptually, genomes are similar to CliffsNotes and other study guides. When students read these short summaries, they know about what happened in a book, without actually reading that book. And that’s how we should be designing the next generation of robots if we ever want them to act like humans, Zador says. “We should give them a set of behavioral CliffsNotes, which they can then unwrap into brain-like structures.” Robots that have such brain-like structures will acquire a set of basic rules to generate basic behaviors and use them to learn more complex ones.
Currently Zador is in the process of developing algorithms that function like simple rules that generate such behaviors. “My algorithms would write these CliffsNotes, outlining how to solve a particular problem,” he explains. “And then, the neural networks will use these CliffsNotes to figure out which ones are useful and use them in their behaviors.” That’s how all living beings operate. They use the pre-programmed info from their genetics to adapt to their changing environments and learn what’s necessary to survive and thrive in these settings.
For example, a robot’s neural network could draw from CliffsNotes with “genetic” instructions for how to be aware of its own body or learn to adjust its movements. And other, different sets of CliffsNotes may imbue it with the basics of physical safety or the fundamentals of speech.
At the moment, Zador is working on algorithms that are trying to mimic neuronal blueprints for very simple organisms—such as earthworms, which have only 302 neurons and about 7000 synapses compared to the millions we have. That’s how evolution worked, too—expanding the brains from simple creatures to more complex to the Homo Sapiens. But if it took millions of years to arrive at modern humans, how long would it take scientists to forge a robot with human intelligence? That’s a billion-dollar question. Yet, Zador is optimistic. “My hypotheses is that if you can build simple organisms that can interact with the world, then the higher level functions will not be nearly as challenging as they currently are.”
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.
Podcast: Wellness chatbots and meditation pods with Deepak Chopra
Over the last few decades, perhaps no one has impacted healthy lifestyles more than Deepak Chopra. While several of his theories and recommendations have been criticized by prominent members of the scientific community, he has helped bring meditation, yoga and other practices for well-being into the mainstream in ways that benefit the health of vast numbers of people every day. His work has led many to accept new ways of thinking about alternative medicine, the power of mind over body, and the malleability of the aging process.
His impact is such that it's been observed our culture no longer recognizes him as a human being but as a pervasive symbol of new-agey personal health and spiritual growth. Last week, I had a chance to confirm that Chopra is, in fact, a human being – and deserving of his icon status – when I talked with him for the Leaps.org podcast. He relayed ideas that were wise and ancient, yet highly relevant to our world today, with the fluidity and ease of someone discussing the weather. Showing no signs of slowing down at age 76, he described his prolific work, including the publication of two books in the past year and a range of technologies he’s developing, including a meditation app, meditation pods for the workplace, and a chatbot for mental health called Piwi.
Take a listen and get inspired to do some meditation and deep thinking on the future of health. As Chopra told me, “If you don’t have time to meditate once per day, you probably need to meditate twice per day.”
Highlights:
2:10: Chopra talks about meditation broadly and meditation pods, including the ones made by OpenSeed for meditation in the workplace.
6:10: The drawbacks of quick fixes like drugs for mental health.
10:30: The benefits of group meditation versus individual meditation.
14:35: What is a "metahuman" and how to become one.
19:40: The difference between the conditioned mind and the mind that's infinitely creative.
22:48: How Chopra's views of free will differ from the views of many neuroscientists.
28:04: Thinking Fast and Slow, and the role of intuition.
31:20: Athletic and creative geniuses.
32:43: The nature of fundamental truth.
34:00: Meditation for kids.
37:12: Never alone.Love and how AI chatbots can support mental health.
42:30: Extending lifespan, gene editing and lifestyle.
46:05: Chopra's mentor in living a long good life (and my mentor).
47:45: The power of yoga.
Links:
- OpenSeed meditation pods for people to meditate at work (Chopra is an advisor to OpenSeed).
- Chopra's book from 2021, Metahuman: Unleash Your Infinite Potential
- Chopra's book from 2022, Abundance: The Inner Path to Wealth
- NeverAlone.Love, Chopra's collaboration of businesses, policy makers, mental health professionals and others to raise awareness about mental health, advance scientific research and "create a global technology platform to democratize access to resources."
- The Piwi chatbot for mental health
- The Chopra Meditation & Well-Being App for people of all ages
- Only 1.6 percent of U.S. children meditate, according to the National Center for Complementary and Integrative Health