COVID Variants Are Like “a Thief Changing Clothes” – and Our Camera System Barely Exists
Whether it's "natural selection" as Darwin called it, or it's "mutating" as the X-Men called it, living organisms change over time, developing thumbs or more efficient protein spikes, depending on the organism and the demands of its environment. The coronavirus that causes COVID-19, SARS-CoV-2, is not an exception, and now, after the virus has infected millions of people around the globe for more than a year, scientists are beginning to see those changes.
The notorious variants that have popped up include B.1.1.7, sometimes called the UK variant, as well as P.1 and B.1.351, which seem to have emerged in Brazil and South Africa respectively. As vaccinations are picking up pace, officials are warning that now
is not the time to become complacent or relax restrictions because the variants aren't well understood.
Some appear to be more transmissible, and deadlier, while others can evade the immune system's defenses better than earlier versions of the virus, potentially undermining the effectiveness of vaccines to some degree. Genomic surveillance, the process of sequencing the genetic code of the virus widely to observe changes and patterns, is a critical way that scientists can keep track of its evolution and work to understand how the variants might affect humans.
"It's like a thief changing clothes"
It's important to note that viruses mutate all the time. If there were funding and personnel to sequence the genome of every sample of the virus, scientists would see thousands of mutations. Not every variant deserves our attention. The vast majority of mutations are not important at all, but recognizing those that are is a crucial tool in getting and staying ahead of the virus. The work of sequencing, analyzing, observing patterns, and using public health tools as necessary is complicated and confusing to those without years of specialized training.
Jeremy Kamil, associate professor of microbiology and immunology at LSU Health Shreveport, in Louisiana, says that the variants developing are like a thief changing clothes. The thief goes in your house, steals your stuff, then leaves and puts on a different shirt and a wig, in the hopes you won't recognize them. Genomic surveillance catches the "thief" even in those different clothes.
One of the tricky things about variants is recognizing the point at which they move from interesting, to concerning at a local level, to dangerous in a larger context.
Understanding variants, both the uninteresting ones and the potentially concerning ones, gives public health officials and researchers at different levels a useful set of tools. Locally, knowing which variants are circulating in the community helps leaders know whether mask mandates and similar measures should be implemented or discontinued, or whether businesses and schools can open relatively safely.
There's more to it than observing new variants
Analysis is complex, particularly when it comes to understanding which variants are of concern. "So the question is always if a mutation becomes common, is that a random occurrence?" says Phoebe Lostroh, associate professor of molecular biology at Colorado College. "Or is the variant the result of some kind of selection because the mutation changes some property about the virus that makes it reproduce more quickly than variants of the virus that don't have that mutation? For a virus, [mutations can affect outcomes like] how much it replicates inside a person's body, how much somebody breathes it out, whether the particles that somebody might breathe in get smaller and can lead to greater transmission."
Along with all of those factors, accurate and useful genomic surveillance requires an understanding of where variants are occurring, how they are related, and an examination of why they might be prevalent.
For example, if a potentially worrisome variant appears in a community and begins to spread very quickly, it's not time to raise a public health alarm until several important questions have been answered, such as whether the variant is spreading due to specific events, or if it's happening because the mutation has allowed the virus to infect people more efficiently. Kamil offered a hypothetical scenario to explain: Imagine that a member of a community became infected and the virus mutated. That person went to church and three more people were infected, but one of them went to a karaoke bar and while singing infected 100 other people. Examining the conditions under which the virus has spread is, therefore, an essential part of untangling whether a mutation itself made the virus more transmissible or if an infected person's behaviors contributed to a local outbreak.
One of the tricky things about variants is recognizing the point at which they move from interesting, to concerning at a local level, to dangerous in a larger context. Genomic sequencing can help with that, but only when it's coordinated. When the same mutation occurs frequently, but is localized to one region, it's a concern, but when the same mutation happens in different places at the same time, it's much more likely that the "virus is learning that's a good mutation," explains Kamil.
The process is called convergent evolution, and it was a fascinating topic long before COVID. Just as your heritage can be traced through DNA, so can that of viruses, and when separate lineages develop similar traits it's almost like scientists can see evolution happening in real time. A mutation to SARS-CoV-2 that happens in more than one place at once is a mutation that makes it easier in some way for the virus to survive and that is when it may become alarming. The widespread, documented variants P.1 and B.1.351 are examples of convergence because they share some of the same virulent mutations despite having developed thousands of miles apart.
However, even variants that are emerging in different places at the same time don't present the kind of threat SARS-CoV-2 did in 2019. "This is nature," says Kamil. "It just means that this virus will not easily be driven to extinction or complete elimination by vaccines." Although a person who has already had COVID-19 can be reinfected with a variant, "it is almost always much milder disease" than the original infection, Kamil adds. Rather than causing full-fledged disease, variants have the potiental to "penetrate herd immunity, spreading relatively quietly among people who have developed natural immunity or been vaccinated, until the virus finds someone who has no immunity yet, and that person would be at risk of hospitalization-grade severe disease or death."
Surveillance and predictions
According to Lostroh, genomic surveillance can help scientists predict what's going to happen. "With the British strain, for instance, that's more transmissible, you can measure how fast it's doubling in the population and you can sort of tell whether we should take more measures against this mutation. Should we shut things down a little longer because that mutation is present in the population? That could be really useful if you did enough sampling in the population that you knew where it was," says Lostroh. If, for example, the more transmissible strain was present in 50 percent of cases, but in another county or state it was barely present, it would allow for rolling lockdowns instead of sweeping measures.
Variants are also extremely important when it comes to the development, manufacture, and distribution of vaccines. "You're also looking at medical countermeasures, such as whether your vaccine is still effective, or if your antiviral needs to be updated," says Lane Warmbrod, a senior analyst and research associate at Johns Hopkins Center for Health Security.
Properly funded and extensive genomic surveillance could eventually help control endemic diseases, too, like the seasonal flu, or other common respiratory infections. Kamil says he envisions a future in which genomic surveillance allows for prediction of sickness just as the weather is predicted today. "It's a 51 for infection today at the San Francisco Airport. There's been detection of some respiratory viruses," he says, offering an example. He says that if you're a vulnerable person, if you're immune-suppressed for some reason, you may want to wear a mask based on the sickness report.
The U.S. has the ability, but lacks standards
The benefits of widespread genomic surveillance are clear, and the United States certainly has the necessary technology, equipment, and personnel to carry it out. But, it's not happening at the speed and extent it needs to for the country to gain the benefits.
"The numbers are improving," said Kamil. "We're probably still at less than half a percent of all the samples that have been taken have been sequenced since the beginning of the pandemic."
Although there's no consensus on how many sequences is ideal for a robust surveillance program, modeling performed by the company Illumina suggests about 5 percent of positive tests should be sequenced. The reasons the U.S. has lagged in implementing a sequencing program are complex and varied, but solvable.
Perhaps the most important element that is currently missing is leadership. In order to conduct an effective genomic surveillance program, there need to be standards. The Johns Hopkins Center for Health Security recently published a paper with recommendations as to what kinds of elements need to be standardized in order to make the best use of sequencing technology and analysis.
"Along with which bioinformatic pipelines you're going to use to do the analyses, which sequencing strategy protocol are you going to use, what's your sampling strategy going to be, how is the data is going to be reported, what data gets reported," says Warmbrod. Currently, there's no guidance from the CDC on any of those things. So, while scientists can collect and report information, they may be collecting and reporting different information that isn't comparable, making it less useful for public health measures and vaccine updates.
Globally, one of the most important tools in making the information from genomic surveillance useful is GISAID, a platform designed for scientists to share -- and, importantly, to be credited for -- their data regarding genetic sequences of influenza. Originally, it was launched as a database of bird flu sequences, but has evolved to become an essential tool used by the WHO to make flu vaccine virus recommendations each year. Scientists who share their credentials have free access to the database, and anyone who uses information from the database must credit the scientist who uploaded that information.
Safety, logistics, and funding matter
Scientists at university labs and other small organizations have been uploading sequences to GISAID almost from the beginning of the pandemic, but their funding is generally limited, and there are no standards regarding information collection or reporting. Private, for-profit labs haven't had motivation to set up sequencing programs, although many of them have the logistical capabilities and funding to do so. Public health departments are understaffed, underfunded, and overwhelmed.
University labs may also be limited by safety concerns. The SARS-CoV-2 virus is dangerous, and there's a question of how samples should be transported to labs for sequencing.
Larger, for-profit organizations often have the tools and distribution capabilities to safely collect and sequence samples, but there hasn't been a profit motive. Genomic sequencing is less expensive now than ever before, but even at $100 per sample, the cost adds up -- not to mention the cost of employing a scientist with the proper credentials to analyze the sequence.
The path forward
The recently passed COVID-19 relief bill does have some funding to address genomic sequencing. Specifically, the American Rescue Plan Act includes $1.75 billion in funding for the Centers for Disease Control and Prevention's Advanced Molecular Detection (AMD) program. In an interview last month, CDC Director Rochelle Walensky said that the additional funding will be "a dial. And we're going to need to dial it up." AMD has already announced a collaboration called the Sequencing for Public Health Emergency Response, Epidemiology, and Surveillance (SPHERES) Initiative that will bring together scientists from public health, academic, clinical, and non-profit laboratories across the country with the goal of accelerating sequencing.
Such a collaboration is a step toward following the recommendations in the paper Warmbrod coauthored. Building capacity now, creating a network of labs, and standardizing procedures will mean improved health in the future. "I want to be optimistic," she says. "The good news is there are a lot of passionate, smart, capable people who are continuing to work with government and work with different stakeholders." She cautions, however, that without a national strategy we won't succeed.
"If we maximize the potential and create that framework now, we can also use it for endemic diseases," she says. "It's a very helpful system for more than COVID if we're smart in how we plan it."
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.
Picture this: your medical first responder descends from the sky like a friendly, unmanned starship. Hovering over your door, it drops a device with recorded instructions to help a bystander jumpstart your heart that has stopped. This, after the 911 call but before the ambulance arrives.
This is exactly what happened on Dec. 9, 2021, when a 71-year-old man in Sweden suffered a cardiac arrest while shoveling snow. A passerby, seeing him collapse, called for an ambulance. In just over three minutes, a drone swooped overhead carrying an Automated External Defibrillator (AED). The patient was revived on the spot before the ambulance arrived to rush him to the hospital where he made a full recovery. The revolutionary technology saved his life.
In 2020, Sweden became the first country to deploy drones carrying AEDs to people in sudden cardiac arrest, when survival odds depend on getting CPR and an electric shock to the heart from a defibrillator within 5 minutes—nearly always before emergency responders arrive.
In the U.S. alone, more than 356,00 cardiac arrests occur outside of hospitals each year; 9 out of 10 of these people die. Plus, the risk of permanent brain injury increases after the first three minutes the heart stops beating. After nine minutes, damage to the brain and other organs is usually severe and irreversible.
“The fundamental technology can be applied to a lot of other emergency situations.”
Once the stuff of sci fi, the delivery of life-saving medical equipment by drone will be commonplace in the near future, experts say. The Swedish team is hailing their study as the first-ever proof of concept for using drones in emergency medicine. The drones arrived only two minutes before the ambulance in most cases but that’s significant during cardiac arrest when survival rates drop 10% every minute.
Since that 2020 pilot, the drones have been tweaked for better performance. They can travel faster and after dark today, and route planning has been optimized, says Mats Sällström, chief executive officer of Everdrone, the technical and development guru for the project, who is collaborating with researchers at the Karolinska Institutet and Sweden’s national emergency call center, SOS Alarm.
When an emergency call comes in, the operator determines if it’s a cardiac arrest. If so, the caller gets CPR instructions while an ambulance is summoned and a control center is notified automatically to dispatch a drone. If conditions allow, the drone flies to the scene via a GPS signal from the caller’s cell phone. Once dropped at the location, the AED beeps to signal its arrival. The AED talks the user through every step when it’s opened while the emergency operator offers support.
Public health officials have tried placing AEDs in public spaces like airports and shopping malls for quick access but the results have been disappointing. Poor usage rates of 2% to 3% have been attributed to bystanders not knowing where they are, not wanting to leave victims, or the site being closed when needed.
Some people fear they could harm the victim or won’t know how to use the AED but not to worry, says Wayne Rosamond, a professor of epidemiology at the University of North Carolina Gillings School of Global Public Health, who studies AED drones. “[The device] won’t shock someone unless they need to be shocked,” he says.
The AED instructions are foolproof, echoes Timothy Chan, professor of engineering at the University of Toronto, who has been building optimization models to design drone networks in Ontario, Canada. All the same, he says, community education will be essential for success. “People have more awareness about drones than AEDs,” he’s found.
Rosamond and Chan are among scientists around the world inspired by Sweden to do their own modeling, simulation and feasibility studies on drone-delivered AEDs.
“Scandinavia is way ahead of us,” notes Rosamond. “There is a tremendous amount of regulatory control over flying drones in the U.S.” In addition to Federal Aviation Administration restrictions, medical drones in the U.S. must comply with HIPAA laws surrounding confidentiality and security of patient information.
To date, Sweden has expanded drone operations and home bases around the country and throughout Europe. Since April 2021, the team has deployed 1-4 drones per week, says Sällström.
Certain weather conditions remain an obstacle. The drones cannot be dispatched safely in rain, snow and heavy wind. Close, heavily populated neighborhoods with high-rise buildings also present challenges.
“Semi-urban areas with residential low-rise [1-5 stories] buildings are the sweet spot for our operations,” Sällström says. “However, as the system matures, we will pursue operations in practically all-weather conditions and also in densely populated areas.” The team is also trying to improve drone speed and battery life to enable flights to rural and remote areas in the future.
Chan predicts that delivering AEDs via drone will be a regular occurrence in five years. In addition, he says, “The fundamental technology can be applied to a lot of other emergency situations.”
Drones could carry medications for anaphylactic shock and opioid overdose, or bring tourniquets and bandages to trauma victims, Chan suggests. Other researchers are looking at the delivery of glucose for low blood sugar emergencies and the transport of organs for transplant.
The sky is no longer the limit.