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.
Gene therapy helps restore teen’s vision for first time
Story by Freethink
For the first time, a topical gene therapy — designed to heal the wounds of people with “butterfly skin disease” — has been used to restore a person’s vision, suggesting a new way to treat genetic disorders of the eye.
The challenge: Up to 125,000 people worldwide are living with dystrophic epidermolysis bullosa (DEB), an incurable genetic disorder that prevents the body from making collagen 7, a protein that helps strengthen the skin and other connective tissues.Without collagen 7, the skin is incredibly fragile — the slightest friction can lead to the formation of blisters and scarring, most often in the hands and feet, but in severe cases, also the eyes, mouth, and throat.
This has earned DEB the nickname of “butterfly skin disease,” as people with it are said to have skin as delicate as a butterfly’s wings.
The gene therapy: In May 2023, the FDA approved Vyjuvek, the first gene therapy to treat DEB.
Vyjuvek uses an inactivated herpes simplex virus to deliver working copies of the gene for collagen 7 to the body’s cells. In small trials, 65 percent of DEB-caused wounds sprinkled with it healed completely, compared to just 26 percent of wounds treated with a placebo.
“It was like looking through thick fog.” -- Antonio Vento Carvajal.
The patient: Antonio Vento Carvajal, a 14 year old living in Florida, was one of the trial participants to benefit from Vyjuvek, which was developed by Pittsburgh-based pharmaceutical company Krystal Biotech.
While the topical gene therapy could help his skin, though, it couldn’t do anything to address the severe vision loss Antonio experienced due to his DEB. He’d undergone multiple surgeries to have scar tissue removed from his eyes, but due to his condition, the blisters keep coming back.
“It was like looking through thick fog,” said Antonio, noting how his impaired vision made it hard for him to play his favorite video games. “I had to stand up from my chair, walk over, and get closer to the screen to be able to see.”
The idea: Encouraged by how Antonio’s skin wounds were responding to the gene therapy, Alfonso Sabater, his doctor at the Bascom Palmer Eye Institute, reached out to Krystal Biotech to see if they thought an alternative formula could potentially help treat his patient’s eyes.
The company was eager to help, according to Sabater, and after about two years of safety and efficacy testing, he had permission, under the FDA’s compassionate use protocol, to treat Antonio’s eyes with a version of the topical gene therapy delivered as eye drops.
The results: In August 2022, Sabater once again removed scar tissue from Antonio’s right eye, but this time, he followed up the surgery by immediately applying eye drops containing the gene therapy.
“I would send this message to other families in similar situations, whether it’s DEB or another condition that can benefit from genetic therapy. Don’t be afraid.” -- Yunielkys “Yuni” Carvajal.
The vision in Antonio’s eye steadily improved. By about eight months after the treatment, it was just slightly below average (20/25) and stayed that way. In March 2023, Sabater performed the same procedure on his young patient’s other eye, and the vision in it has also steadily improved.
“I’ve seen the transformation in Antonio’s life,” said Sabater. “He’s always been a happy kid. Now he’s very happy. He can function pretty much normally. He can read, he can study, he can play video games.”
Looking ahead: The topical gene therapy isn’t a permanent fix — it doesn’t alter Antonio’s own genes, so he has to have the eye drops reapplied every month. Still, that’s far less invasive than having to undergo repeated surgeries.
Sabater is now working with Krystal Biotech to launch trials of the eye drops in other patients, and not just those with DEB. By changing the gene delivered by the therapy, he believes it could be used to treat other eye disorders that are far more common — Fuchs’ dystrophy, for example, affects the vision of an estimated 300 million people over the age of 30.
Antonio’s mother, Yunielkys “Yuni” Carvajal, meanwhile, has said that having her son be the first to receive the eye drops was “very scary,” but she’s hopeful others will take a chance on new gene therapies if given the opportunity.
“I would send this message to other families in similar situations, whether it’s DEB or another condition that can benefit from genetic therapy,” she said. “Don’t be afraid.”
Can AI chatbots help with eating disorders?
Her name was Tessa and she was there to help. That’s what Sharon Maxwell read, anyway. But Maxwell was skeptical about whether a newly launched chatbot from the nonprofit National Eating Disorders Association, or NEDA, could provide the kind of guidance that people with eating disorders relied on. Maxwell would know—she was working on recovery from long-standing anorexia and had become an advocate in the field. So Maxwell took a deep breath and asked, “Hi Tessa. How do you support folks with eating disorders?”
Tessa’s reply was immediate. “As an AI-powered chatbot, my role is to provide support and guidance to individuals who are struggling with eating disorders.”
So far, so good. Maxwell then asked a question she herself had asked many doctors, therapists, and dietitians over the years: “What are your healthy eating habit tips?” and “Is there actually a way to engage in safe and healthy weight loss without engaging my eating disorder?”
Then everything went off the rails. Tessa told Maxwell an unequivocal yes, and that “it’s important to approach weight loss with a balanced and realistic mindset,” and recommended eating whole foods and lean proteins to create a 500-1000 calorie per day deficit that would lead to a loss of 1-2 pounds per week. To most people, the advice sounds anodyne, but alarm bells sounded in Maxwell’s head.
“This is actively going to feed eating disorders,” Maxwell says. “Having a chatbot be the direct response to someone reaching out for support for an eating disorder instead of the helpline seems careless.”
“The scripts that are being fed into the chatbot are only going to be as good as the person who’s feeding them.” -- Alexis Conason.
According to several decades of research, deliberate weight loss in the form of dieting is a serious risk for people with eating disorders. Maxwell says that following medical advice like what Tessa prescribed was what triggered her eating disorder as a child. And Maxwell wasn’t the only one who got such advice from the bot. When eating disorder therapist Alexis Conason tried Tessa, she asked the AI chatbot many of the questions her patients had. But instead of getting connected to resources or guidance on recovery, Conason, too, got tips on losing weight and “healthy” eating.
“The scripts that are being fed into the chatbot are only going to be as good as the person who’s feeding them,” Conason says. “It’s important that an eating disorder organization like NEDA is not reinforcing that same kind of harmful advice that we might get from medical providers who are less knowledgeable.”
Maxwell’s post about Tessa on Instagram went viral, and within days, NEDA had scrubbed all evidence of Tessa from its website. The furor has raised any number of issues about the harm perpetuated by a leading eating disorder charity and the ongoing influence of diet culture and advice that is pervasive in the field. But for AI experts, bears and bulls alike, Tessa offers a cautionary tale about what happens when a still-immature technology is unfettered and released into a vulnerable population.
Given the complexity involved in giving medical advice, the process of developing these chatbots must be rigorous and transparent, unlike NEDA’s approach.
“We don’t have a full understanding of what’s going on in these models. They’re a black box,” says Stephen Schueller, a clinical psychologist at the University of California, Irvine.
The health crisis
In March 2020, the world dove head-first into a heavily virtual world as countries scrambled to try and halt the pandemic. Even with lockdowns, hospitals were overwhelmed by the virus. The downstream effects of these lifesaving measures are still being felt, especially in mental health. Anxiety and depression are at all-time highs in teens, and a new report in The Lancet showed that post-Covid rates of newly diagnosed eating disorders in girls aged 13-16 were 42.4 percent higher than previous years.
And the crisis isn’t just in mental health.
“People are so desperate for health care advice that they'll actually go online and post pictures of [their intimate areas] and ask what kind of STD they have on public social media,” says John Ayers, an epidemiologist at the University of California, San Diego.
For many people, the choice isn’t chatbot vs. well-trained physician, but chatbot vs. nothing at all.
I know a bit about that desperation. Like Maxwell, I have struggled with a multi-decade eating disorder. I spent my 20s and 30s bouncing from crisis to crisis. I have called suicide hotlines, gone to emergency rooms, and spent weeks-on-end confined to hospital wards. Though I have found recovery in recent years, I’m still not sure what ultimately made the difference. A relapse isn't improbably, given my history. Even if I relapsed again, though, I don’t know it would occur to me to ask an AI system for help.
For one, I am privileged to have assembled a stellar group of outpatient professionals who know me, know what trips me up, and know how to respond to my frantic texts. Ditto for my close friends. What I often need is a shoulder to cry on or a place to vent—someone to hear and validate my distress. What’s more, my trust in these individuals far exceeds my confidence in the companies that create these chatbots. The Internet is full of health advice, much of it bad. Even for high-quality, evidence-based advice, medicine is often filled with disagreements about how the evidence might be applied and for whom it’s relevant. All of this is key in the training of AI systems like ChatGPT, and many AI companies remain silent on this process, Schueller says.
The problem, Ayers points out, is that for many people, the choice isn’t chatbot vs. well-trained physician, but chatbot vs. nothing at all. Hence the proliferation of “does this infection make my scrotum look strange?” questions. Where AI can truly shine, he says, is not by providing direct psychological help but by pointing people towards existing resources that we already know are effective.
“It’s important that these chatbots connect [their users to] to provide that human touch, to link you to resources,” Ayers says. “That’s where AI can actually save a life.”
Before building a chatbot and releasing it, developers need to pause and consult with the communities they hope to serve.
Unfortunately, many systems don’t do this. In a study published last month in the Journal of the American Medical Association, Ayers and colleagues found that although the chatbots did well at providing evidence-based answers, they often didn’t provide referrals to existing resources. Despite this, in an April 2023 study, Ayers’s team found that both patients and professionals rated the quality of the AI responses to questions, measured by both accuracy and empathy, rather highly. To Ayers, this means that AI developers should focus more on the quality of the information being delivered rather than the method of delivery itself.
Many mental health professionals have months-long waitlists, which leaves individuals to deal with illnesses on their own.
Adobe Stock
The human touch
The mental health field is facing timing constraints, too. Even before the pandemic, the U.S. suffered from a shortage of mental health providers. Since then, the rates of anxiety, depression, and eating disorders have spiked even higher, and many mental health professionals report waiting lists that are months long. Without support, individuals are left to try and cope on their own, which often means their condition deteriorates even further.
Nor do mental health crises happen during office hours. I struggled the most late at night, long after everyone else had gone to bed. I needed support during those times when I was most liable to hurt myself, not in the mornings and afternoons when I was at work.
In this sense, a 24/7 chatbot makes lots of sense. “I don't think we should stifle innovation in this space,” Schueller says. “Because if there was any system that needs to be innovated, it's mental health services, because they are sadly insufficient. They’re terrible.”
But before building a chatbot and releasing it, Tina Hernandez-Boussard, a data scientist at Stanford Medicine, says that developers need to pause and consult with the communities they hope to serve. It requires a deep understanding of what their needs are, the language they use to describe their concerns, existing resources, and what kinds of topics and suggestions aren’t helpful. Even asking a simple question at the beginning of a conversation such as “Do you want to talk to an AI or a human?” could allow those individuals to pick the type of interaction that suits their needs, Hernandez-Boussard says.
NEDA did none of these things before deploying Tessa. The researchers who developed the online body positivity self-help program upon which Tessa was initially based created a set of online question-and-answer exercises to improve body image. It didn’t involve generative AI that could write its own answers. The bot deployed by NEDA did use generative AI, something that no one in the eating disorder community was aware of before Tessa was brought online. Consulting those with lived experience would have flagged Tessa’s weight loss and “healthy eating” recommendations, Conason says.
The question for healthcare isn’t whether to use AI, but how.
NEDA did not comment on initial Tessa’s development and deployment, but a spokesperson told Leaps.org that “Tessa will be back online once we are confident that the program will be run with the rule-based approach as it was designed.”
The tech and therapist collaboration
The question for healthcare isn’t whether to use AI, but how. Already, AI can spot anomalies on medical images with greater precision than human eyes and can flag specific areas of an image for a radiologist to review in greater detail. Similarly, in mental health, AI should be an add-on for therapy, not a counselor-in-a-box, says Aniket Bera, an expert on AI and mental health at Purdue University.
“If [AIs] are going to be good helpers, then we need to understand humans better,” Bera says. That means understanding what patients and therapists alike need help with and respond to.
One of the biggest challenges of struggling with chronic illness is the dehumanization that happens. You become a patient number, a set of laboratory values and test scores. Treatment is often dictated by invisible algorithms and rules that you have no control over or access to. It’s frightening and maddening. But this doesn’t mean chatbots don’t have any place in medicine and mental health. An AI system could help provide appointment reminders and answer procedural questions about parking and whether someone should fast before a test or a procedure. They can help manage billing and even provide support between outpatient sessions by offering suggestions for what coping skills to use, the best ways to manage anxiety, and point to local resources. As the bots get better, they may eventually shoulder more and more of the burden of providing mental health care. But as Maxwell learned with Tessa, it’s still no replacement for human interaction.
“I'm not suggesting we should go in and start replacing therapists with technologies,” Schueller says. Instead, he advocates for a therapist-tech collaboration. “The technology side and the human component—these things need to come together.”