The Science of Why Adjusting to Omicron Is So Tough
We are sticking our heads into the sand of reality on Omicron, and the results may be catastrophic.
Omicron is over 4 times more infectious than Delta. The Pfizer two-shot vaccine offers only 33% protection from infection. A Pfizer booster vaccine does raises protection to about 75%, but wanes to around 30-40 percent 10 weeks after the booster.
The only silver lining is that Omicron appears to cause a milder illness than Delta. Yet the World Health Organization has warned about the “mildness” narrative.
That’s because the much faster disease transmission and vaccine escape undercut the less severe overall nature of Omicron. That’s why hospitals have a large probability of being overwhelmed, as the Center for Disease Control warned, in this major Omicron wave.
Yet despite this very serious threat, we see the lack of real action. The federal government tightened international travel guidelines and is promoting boosters. Certainly, it’s crucial to get as many people to get their booster – and initial vaccine doses – as soon as possible. But the government is not taking the steps that would be the real game-changers.
Pfizer’s anti-viral drug Paxlovid decreases the risk of hospitalization and death from COVID by 89%. Due to this effectiveness, the FDA approved Pfizer ending the trial early, because it would be unethical to withhold the drug from people in the control group. Yet the FDA chose not to hasten the approval process along with the emergence of Omicron in late November, only getting around to emergency authorization in late December once Omicron took over. That delay meant the lack of Paxlovid for the height of the Omicron wave, since it takes many weeks to ramp up production, resulting in an unknown number of unnecessary deaths.
We humans are prone to falling for dangerous judgment errors called cognitive biases.
Widely available at-home testing would enable people to test themselves quickly, so that those with mild symptoms can quarantine instead of infecting others. Yet the federal government did not make tests available to patients when Omicron emerged in late November. That’s despite the obviousness of the coming wave based on the precedent of South Africa, UK, and Denmark and despite the fact that the government made vaccines freely available. Its best effort was to mandate that insurance cover reimbursements for these kits, which is way too much of a barrier for most people. By the time Omicron took over, the federal government recognized its mistake and ordered 500 million tests to be made available in January. However, that’s far too late. And the FDA also played a harmful role here, with its excessive focus on accuracy going back to mid-2020, blocking the widespread availability of cheap at-home tests. By contrast, Europe has a much better supply of tests, due to its approval of quick and slightly less accurate tests.
Neither do we see meaningful leadership at the level of employers. Some are bringing out the tired old “delay the office reopening” play. For example, Google, Uber, and Ford, along with many others, have delayed the return to the office for several months. Those that already returned are calling for stricter pandemic measures, such as more masks and social distancing, but not changing their work arrangements or adding sufficient ventilation to address the spread of COVID.
Despite plenty of warnings from risk management and cognitive bias experts, leaders are repeating the same mistakes we fell into with Delta. And so are regular people. For example, surveys show that Omicron has had very little impact on the willingness of unvaccinated Americans to get a first vaccine dose, or of vaccinated Americans to get a booster. That’s despite Omicron having taken over from Delta in late December.
What explains this puzzling behavior on both the individual and society level? We humans are prone to falling for dangerous judgment errors called cognitive biases. Rooted in wishful thinking and gut reactions, these mental blindspots lead to poor strategic and financial decisions when evaluating choices.
These cognitive biases stem from the more primitive, emotional, and intuitive part of our brains that ensured survival in our ancestral environment. This quick, automatic reaction of our emotions represents the autopilot system of thinking, one of the two systems of thinking in our brains. It makes good decisions most of the time but also regularly makes certain systematic thinking errors, since it’s optimized to help us survive. In modern society, our survival is much less at risk, and our gut is more likely to compel us to focus on the wrong information to make decisions.
One of the biggest challenges relevant to Omicron is the cognitive bias known as the ostrich effect. Named after the myth that ostriches stick their heads into the sand when they fear danger, the ostrich effect refers to people denying negative reality. Delta illustrated the high likelihood of additional dangerous variants, yet we failed to pay attention to and prepare for such a threat.
We want the future to be normal. We’re tired of the pandemic and just want to get back to pre-pandemic times. Thus, we greatly underestimate the probability and impact of major disruptors, like new COVID variants. That cognitive bias is called the normalcy bias.
When we learn one way of functioning in any area, we tend to stick to that way of functioning. You might have heard of this as the hammer-nail syndrome: when you have a hammer, everything looks like a nail. That syndrome is called functional fixedness. This cognitive bias causes those used to their old ways of action to reject any alternatives, including to prepare for a new variant.
Our minds naturally prioritize the present. We want what we want now, and downplay the long-term consequences of our current desires. That fallacious mental pattern is called hyperbolic discounting, where we excessively discount the benefits of orienting toward the future and focus on the present. A clear example is focusing on the short-term perceived gains of trying to return to normal over managing the risks of future variants.
The way forward into the future is to defeat cognitive biases and avoid denying reality by rethinking our approach to the future.
The FDA requires a serious overhaul. It’s designed for a non-pandemic environment, where the goal is to have a highly conservative, slow-going, and risk-averse approach so that the public feels confident trusting whatever it approved. That’s simply unacceptable in a fast-moving pandemic, and we are bound to face future pandemics in the future.
The federal government needs to have cognitive bias experts weigh in on federal policy. Putting all of its eggs in one basket – vaccinations – is not a wise move when we face the risks of a vaccine-escaping variant. Its focus should also be on expediting and prioritizing anti-virals, scaling up cheap rapid testing, and subsidizing high-filtration masks.
For employers, instead of dictating a top-down approach to how employees collaborate, companies need to adopt a decentralized team-led approach. Each individual team leader of a rank-and-file employee team should determine what works best for their team. After all, team leaders tend to know much more of what their teams need, after all. Moreover, they can respond to local emergencies like COVID surges.
At the same time, team leaders need to be trained to integrate best practices for hybrid and remote team leadership. Companies transitioned to telework abruptly as part of the March 2020 lockdowns. They fell into the cognitive bias of functional fixedness and transposed their pre-existing, in-office methods of collaboration on remote work. Zoom happy hours are a clear example: The large majority of employees dislike them, and research shows they are disconnecting, rather than connecting.
Yet supervisors continue to use them, despite the existence of much better methods of facilitating colalboration, which have been shown to work, such as virtual water cooler discussions, virtual coworking, and virtual mentoring. Leaders also need to facilitate innovation in hybrid and remote teams through techniques such as virtual asynchronous brainstorming. Finally, team leaders need to adjust performance evaluation to adapt to the needs of hybrid and remote teams.
On an individual level, people built up certain expectations during the first two years of the pandemic, and they don't apply with Omicron. For example, most people still think that a cloth mask is a fine source of protection. In reality, you really need an N-95 mask, since Omicron is so much more infectious. Another example is that many people don’t realize that symptom onset is much quicker with Omicron, and they aren’t prepared for the consequences.
Remember that we have a huge number of people who are asymptomatic, often without knowing it, due to the much higher mildness of Omicron. About 8% of people admitted to hospitals for other reasons in San Francisco test positive for COVID without symptoms, which we can assume translates for other cities. That means many may think they're fine and they're actually infectious. The result is a much higher chance of someone getting many other people sick.
During this time of record-breaking cases, you need to be mindful about your internalized assumptions and adjust your risk calculus accordingly. So if you can delay higher-risk activities, January and February might be the time to do it. Prepare for waves of disruptions to continue over time, at least through the end of February.
Of course, you might also choose to not worry about getting infected. If you are vaccinated and boosted, and do not have any additional health risks, you are very unlikely to have a serious illness due to Omicron. You can just take the small risk of a serious illness – which can happen – and go about your daily life. If doing so, watch out for those you care about who do have health concerns, since if you infect them, they might not have a mild case even with Omicron.
In short, instead of trying to turn back the clock to the lost world of January 2020, consider how we might create a competitive advantage in our new future. COVID will never go away: we need to learn to live with it. That means reacting appropriately and thoughtfully to new variants and being intentional about our trade-offs.
DNA- and RNA-based electronic implants may revolutionize healthcare
Implantable electronic devices can significantly improve patients’ quality of life. A pacemaker can encourage the heart to beat more regularly. A neural implant, usually placed at the back of the skull, can help brain function and encourage higher neural activity. Current research on neural implants finds them helpful to patients with Parkinson’s disease, vision loss, hearing loss, and other nerve damage problems. Several of these implants, such as Elon Musk’s Neuralink, have already been approved by the FDA for human use.
Yet, pacemakers, neural implants, and other such electronic devices are not without problems. They require constant electricity, limited through batteries that need replacements. They also cause scarring. “The problem with doing this with electronics is that scar tissue forms,” explains Kate Adamala, an assistant professor of cell biology at the University of Minnesota Twin Cities. “Anytime you have something hard interacting with something soft [like muscle, skin, or tissue], the soft thing will scar. That's why there are no long-term neural implants right now.” To overcome these challenges, scientists are turning to biocomputing processes that use organic materials like DNA and RNA. Other promised benefits include “diagnostics and possibly therapeutic action, operating as nanorobots in living organisms,” writes Evgeny Katz, a professor of bioelectronics at Clarkson University, in his book DNA- And RNA-Based Computing Systems.
While a computer gives these inputs in binary code or "bits," such as a 0 or 1, biocomputing uses DNA strands as inputs, whether double or single-stranded, and often uses fluorescent RNA as an output.
Adamala’s research focuses on developing such biocomputing systems using DNA, RNA, proteins, and lipids. Using these molecules in the biocomputing systems allows the latter to be biocompatible with the human body, resulting in a natural healing process. In a recent Nature Communications study, Adamala and her team created a new biocomputing platform called TRUMPET (Transcriptional RNA Universal Multi-Purpose GatE PlaTform) which acts like a DNA-powered computer chip. “These biological systems can heal if you design them correctly,” adds Adamala. “So you can imagine a computer that will eventually heal itself.”
The basics of biocomputing
Biocomputing and regular computing have many similarities. Like regular computing, biocomputing works by running information through a series of gates, usually logic gates. A logic gate works as a fork in the road for an electronic circuit. The input will travel one way or another, giving two different outputs. An example logic gate is the AND gate, which has two inputs (A and B) and two different results. If both A and B are 1, the AND gate output will be 1. If only A is 1 and B is 0, the output will be 0 and vice versa. If both A and B are 0, the result will be 0. While a computer gives these inputs in binary code or "bits," such as a 0 or 1, biocomputing uses DNA strands as inputs, whether double or single-stranded, and often uses fluorescent RNA as an output. In this case, the DNA enters the logic gate as a single or double strand.
If the DNA is double-stranded, the system “digests” the DNA or destroys it, which results in non-fluorescence or “0” output. Conversely, if the DNA is single-stranded, it won’t be digested and instead will be copied by several enzymes in the biocomputing system, resulting in fluorescent RNA or a “1” output. And the output for this type of binary system can be expanded beyond fluorescence or not. For example, a “1” output might be the production of the enzyme insulin, while a “0” may be that no insulin is produced. “This kind of synergy between biology and computation is the essence of biocomputing,” says Stephanie Forrest, a professor and the director of the Biodesign Center for Biocomputing, Security and Society at Arizona State University.
Biocomputing circles are made of DNA, RNA, proteins and even bacteria.
Evgeny Katz
The TRUMPET’s promise
Depending on whether the biocomputing system is placed directly inside a cell within the human body, or run in a test-tube, different environmental factors play a role. When an output is produced inside a cell, the cell's natural processes can amplify this output (for example, a specific protein or DNA strand), creating a solid signal. However, these cells can also be very leaky. “You want the cells to do the thing you ask them to do before they finish whatever their businesses, which is to grow, replicate, metabolize,” Adamala explains. “However, often the gate may be triggered without the right inputs, creating a false positive signal. So that's why natural logic gates are often leaky." While biocomputing outside a cell in a test tube can allow for tighter control over the logic gates, the outputs or signals cannot be amplified by a cell and are less potent.
TRUMPET, which is smaller than a cell, taps into both cellular and non-cellular biocomputing benefits. “At its core, it is a nonliving logic gate system,” Adamala states, “It's a DNA-based logic gate system. But because we use enzymes, and the readout is enzymatic [where an enzyme replicates the fluorescent RNA], we end up with signal amplification." This readout means that the output from the TRUMPET system, a fluorescent RNA strand, can be replicated by nearby enzymes in the platform, making the light signal stronger. "So it combines the best of both worlds,” Adamala adds.
These organic-based systems could detect cancer cells or low insulin levels inside a patient’s body.
The TRUMPET biocomputing process is relatively straightforward. “If the DNA [input] shows up as single-stranded, it will not be digested [by the logic gate], and you get this nice fluorescent output as the RNA is made from the single-stranded DNA, and that's a 1,” Adamala explains. "And if the DNA input is double-stranded, it gets digested by the enzymes in the logic gate, and there is no RNA created from the DNA, so there is no fluorescence, and the output is 0." On the story's leading image above, if the tube is "lit" with a purple color, that is a binary 1 signal for computing. If it's "off" it is a 0.
While still in research, TRUMPET and other biocomputing systems promise significant benefits to personalized healthcare and medicine. These organic-based systems could detect cancer cells or low insulin levels inside a patient’s body. The study’s lead author and graduate student Judee Sharon is already beginning to research TRUMPET's ability for earlier cancer diagnoses. Because the inputs for TRUMPET are single or double-stranded DNA, any mutated or cancerous DNA could theoretically be detected from the platform through the biocomputing process. Theoretically, devices like TRUMPET could be used to detect cancer and other diseases earlier.
Adamala sees TRUMPET not only as a detection system but also as a potential cancer drug delivery system. “Ideally, you would like the drug only to turn on when it senses the presence of a cancer cell. And that's how we use the logic gates, which work in response to inputs like cancerous DNA. Then the output can be the production of a small molecule or the release of a small molecule that can then go and kill what needs killing, in this case, a cancer cell. So we would like to develop applications that use this technology to control the logic gate response of a drug’s delivery to a cell.”
Although platforms like TRUMPET are making progress, a lot more work must be done before they can be used commercially. “The process of translating mechanisms and architecture from biology to computing and vice versa is still an art rather than a science,” says Forrest. “It requires deep computer science and biology knowledge,” she adds. “Some people have compared interdisciplinary science to fusion restaurants—not all combinations are successful, but when they are, the results are remarkable.”
In today’s podcast episode, Leaps.org Deputy Editor Lina Zeldovich speaks about the health and ecological benefits of farming crickets for human consumption with Bicky Nguyen, who joins Lina from Vietnam. Bicky and her business partner Nam Dang operate an insect farm named CricketOne. Motivated by the idea of sustainable and healthy protein production, they started their unconventional endeavor a few years ago, despite numerous naysayers who didn’t believe that humans would ever consider munching on bugs.
Yet, making creepy crawlers part of our diet offers many health and planetary advantages. Food production needs to match the rise in global population, estimated to reach 10 billion by 2050. One challenge is that some of our current practices are inefficient, polluting and wasteful. According to nonprofit EarthSave.org, it takes 2,500 gallons of water, 12 pounds of grain, 35 pounds of topsoil and the energy equivalent of one gallon of gasoline to produce one pound of feedlot beef, although exact statistics vary between sources.
Meanwhile, insects are easy to grow, high on protein and low on fat. When roasted with salt, they make crunchy snacks. When chopped up, they transform into delicious pâtes, says Bicky, who invents her own cricket recipes and serves them at industry and public events. Maybe that’s why some research predicts that edible insects market may grow to almost $10 billion by 2030. Tune in for a delectable chat on this alternative and sustainable protein.
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Further reading:
More info on Bicky Nguyen
https://yseali.fulbright.edu.vn/en/faculty/bicky-n...
The environmental footprint of beef production
https://www.earthsave.org/environment.htm
https://www.watercalculator.org/news/articles/beef-king-big-water-footprints/
https://www.frontiersin.org/articles/10.3389/fsufs.2019.00005/full
https://ourworldindata.org/carbon-footprint-food-methane
Insect farming as a source of sustainable protein
https://www.insectgourmet.com/insect-farming-growing-bugs-for-protein/
https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/insect-farming
Cricket flour is taking the world by storm
https://www.cricketflours.com/
https://talk-commerce.com/blog/what-brands-use-cricket-flour-and-why/
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.