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."
“Virtual Biopsies” May Soon Make Some Invasive Tests Unnecessary
At his son's college graduation in 2017, Dan Chessin felt "terribly uncomfortable" sitting in the stadium. The bouts of pain persisted, and after months of monitoring, a urologist took biopsies of suspicious areas in his prostate.
This innovation may enhance diagnostic precision and promptness, but it also brings ethical concerns to the forefront.
"In my case, the biopsies came out cancerous," says Chessin, 60, who underwent robotic surgery for intermediate-grade prostate cancer at University Hospitals Cleveland Medical Center.
Although he needed a biopsy, as most patients today do, advances in radiologic technology may make such invasive measures unnecessary in the future. Researchers are developing better imaging techniques and algorithms—a form of computer science called artificial intelligence, in which machines learn and execute tasks that typically require human brain power.
This innovation may enhance diagnostic precision and promptness. But it also brings ethical concerns to the forefront of the conversation, highlighting the potential for invasion of privacy, unequal patient access, and less physician involvement in patient care.
A National Academy of Medicine Special Publication, released in December, emphasizes that setting industry-wide standards for use in patient care is essential to AI's responsible and transparent implementation as the industry grapples with voluminous quantities of data. The technology should be viewed as a tool to supplement decision-making by highly trained professionals, not to replace it.
MRI--a test that uses powerful magnets, radio waves, and a computer to take detailed images inside the body--has become highly accurate in detecting aggressive prostate cancer, but its reliability is more limited in identifying low and intermediate grades of malignancy. That's why Chessin opted to have his prostate removed rather than take the chance of missing anything more suspicious that could develop.
His urologist, Lee Ponsky, says AI's most significant impact is yet to come. He hopes University Hospitals Cleveland Medical Center's collaboration with research scientists at its academic affiliate, Case Western Reserve University, will lead to the invention of a virtual biopsy.
A National Cancer Institute five-year grant is funding the project, launched in 2017, to develop a combined MRI and computerized tool to support more accurate detection and grading of prostate cancer. Such a tool would be "the closest to a crystal ball that we can get," says Ponsky, professor and chairman of the Urology Institute.
In situations where AI has guided diagnostics, radiologists' interpretations of breast, lung, and prostate lesions have improved as much as 25 percent, says Anant Madabhushi, a biomedical engineer and director of the Center for Computational Imaging and Personalized Diagnostics at Case Western Reserve, who is collaborating with Ponsky. "AI is very nascent," Madabhushi says, estimating that fewer than 10 percent of niche academic medical centers have used it. "We are still optimizing and validating the AI and virtual biopsy technology."
In October, several North American and European professional organizations of radiologists, imaging informaticists, and medical physicists released a joint statement on the ethics of AI. "Ultimate responsibility and accountability for AI remains with its human designers and operators for the foreseeable future," reads the statement, published in the Journal of the American College of Radiology. "The radiology community should start now to develop codes of ethics and practice for AI that promote any use that helps patients and the common good and should block use of radiology data and algorithms for financial gain without those two attributes."
Overreliance on new technology also poses concern when humans "outsource the process to a machine."
The statement's leader author, radiologist J. Raymond Geis, says "there's no question" that machines equipped with artificial intelligence "can extract more information than two human eyes" by spotting very subtle patterns in pixels. Yet, such nuances are "only part of the bigger picture of taking care of a patient," says Geis, a senior scientist with the American College of Radiology's Data Science Institute. "We have to be able to combine that with knowledge of what those pixels mean."
Setting ethical standards is high on all physicians' radar because the intricacies of each patient's medical record are factored into the computer's algorithm, which, in turn, may be used to help interpret other patients' scans, says radiologist Frank Rybicki, vice chair of operations and quality at the University of Cincinnati's department of radiology. Although obtaining patients' informed consent in writing is currently necessary, ethical dilemmas arise if and when patients have a change of heart about the use of their private health information. It is likely that removing individual data may be possible for some algorithms but not others, Rybicki says.
The information is de-identified to protect patient privacy. Using it to advance research is akin to analyzing human tissue removed in surgical procedures with the goal of discovering new medicines to fight disease, says Maryellen Giger, a University of Chicago medical physicist who studies computer-aided diagnosis in cancers of the breast, lung, and prostate, as well as bone diseases. Physicians who become adept at using AI to augment their interpretation of imaging will be ahead of the curve, she says.
As with other new discoveries, patient access and equality come into play. While AI appears to "have potential to improve over human performance in certain contexts," an algorithm's design may result in greater accuracy for certain groups of patients, says Lucia M. Rafanelli, a political theorist at The George Washington University. This "could have a disproportionately bad impact on one segment of the population."
Overreliance on new technology also poses concern when humans "outsource the process to a machine." Over time, they may cease developing and refining the skills they used before the invention became available, said Chloe Bakalar, a visiting research collaborator at Princeton University's Center for Information Technology Policy.
"AI is a paradigm shift with magic power and great potential."
Striking the right balance in the rollout of the technology is key. Rushing to integrate AI in clinical practice may cause harm, whereas holding back too long could undermine its ability to be helpful. Proper governance becomes paramount. "AI is a paradigm shift with magic power and great potential," says Ge Wang, a biomedical imaging professor at Rensselaer Polytechnic Institute in Troy, New York. "It is only ethical to develop it proactively, validate it rigorously, regulate it systematically, and optimize it as time goes by in a healthy ecosystem."
How Emerging Technologies Can Help Us Fight the New Coronavirus
In nature, few species remain dominant for long. Any sizable population of similar individuals offers immense resources to whichever parasite can evade its defenses, spreading rapidly from one member to the next.
Which will prove greater: our defenses or our vulnerabilities?
Humans are one such dominant species. That wasn't always the case: our hunter-gatherer ancestors lived in groups too small and poorly connected to spread pathogens like wildfire. Our collective vulnerability to pandemics began with the dawn of cities and trade networks thousands of years ago. Roman cities were always demographic sinks, but never more so than when a pandemic agent swept through. The plague of Cyprian, the Antonine plague, the plague of Justinian – each is thought to have killed over ten million people, an appallingly high fraction of the total population of the empire.
With the advent of sanitation, hygiene, and quarantines, we developed our first non-immunological defenses to curtail the spread of plagues. With antibiotics, we began to turn the weapons of microbes against our microbial foes. Most potent of all, we use vaccines to train our immune systems to fight pathogens before we are even exposed. Edward Jenner's original vaccine alone is estimated to have saved half a billion lives.
It's been over a century since we suffered from a swift and deadly pandemic. Even the last deadly influenza of 1918 killed only a few percent of humanity – nothing so bad as any of the Roman plagues, let alone the Black Death of medieval times.
How much of our recent winning streak has been due to luck?
Much rides on that question, because the same factors that first made our ancestors vulnerable are now ubiquitous. Our cities are far larger than those of ancient times. They're inhabited by an ever-growing fraction of humanity, and are increasingly closely connected: we now routinely travel around the world in the course of a day. Despite urbanization, global population growth has increased contact with wild animals, creating more opportunities for zoonotic pathogens to jump species. Which will prove greater: our defenses or our vulnerabilities?
The tragic emergence of coronavirus 2019-nCoV in Wuhan may provide a test case. How devastating this virus will become is highly uncertain at the time of writing, but its rapid spread to many countries is deeply worrisome. That it seems to kill only the already infirm and spare the healthy is small comfort, and may counterintuitively assist its spread: it's easy to implement a quarantine when everyone infected becomes extremely ill, but if carriers may not exhibit symptoms as has been reported, it becomes exceedingly difficult to limit transmission. The virus, a distant relative of the more lethal SARS virus that killed 800 people in 2002 to 2003, has evolved to be transmitted between humans and spread to 18 countries in just six weeks.
Humanity's response has been faster than ever, if not fast enough. To its immense credit, China swiftly shared information, organized and built new treatment centers, closed schools, and established quarantines. The Coalition for Epidemic Preparedness Innovations, which was founded in 2017, quickly funded three different companies to develop three different varieties of vaccine: a standard protein vaccine, a DNA vaccine, and an RNA vaccine, with more planned. One of the agreements was signed after just four days of discussion, far faster than has ever been done before.
The new vaccine candidates will likely be ready for clinical trials by early summer, but even if successful, it will be additional months before the vaccine will be widely available. The delay may well be shorter than ever before thanks to advances in manufacturing and logistics, but a delay it will be.
The 1918 influenza virus killed more than half of its victims in the United Kingdom over just three months.
If we faced a truly nasty virus, something that spreads like pandemic influenza – let alone measles – yet with the higher fatality rate of, say, H7N9 avian influenza, the situation would be grim. We are profoundly unprepared, on many different levels.
So what would it take to provide us with a robust defense against pandemics?
Minimize the attack surface: 2019-nCoV jumped from an animal, most probably a bat, to humans. China has now banned the wildlife trade in response to the epidemic. Keeping it banned would be prudent, but won't be possible in all nations. Still, there are other methods of protection. Influenza viruses commonly jump from birds to pigs to humans; the new coronavirus may have similarly passed through a livestock animal. Thanks to CRISPR, we can now edit the genomes of most livestock. If we made them immune to known viruses, and introduced those engineered traits to domesticated animals everywhere, we would create a firewall in those intermediate hosts. We might even consider heritably immunizing the wild organisms most likely to serve as reservoirs of disease.
None of these defenses will be cheap, but they'll be worth every penny.
Rapid diagnostics: We need a reliable method of detection costing just pennies to be available worldwide inside of a week of discovering a new virus. This may eventually be possible thanks to a technology called SHERLOCK, which is based on a CRISPR system more commonly used for precision genome editing. Instead of using CRISPR to find and edit a particular genome sequence in a cell, SHERLOCK programs it to search for a desired target and initiate an easily detected chain reaction upon discovery. The technology is capable of fantastic sensitivity: with an attomolar (10-18) detection limit, it senses single molecules of a unique DNA or RNA fingerprint, and the components can be freeze-dried onto paper strips.
Better preparations: China acted swiftly to curtail the spread of the Wuhan virus with traditional public health measures, but not everything went as smoothly as it might have. Most cities and nations have never conducted a pandemic preparedness drill. Best give people a chance to practice keeping the city barely functional while minimizing potential exposure events before facing the real thing.
Faster vaccines: Three months to clinical trials is too long. We need a robust vaccine discovery and production system that can generate six candidates within a week of the pathogen's identification, manufacture a million doses the week after, and scale up to a hundred million inside of a month. That may be possible for novel DNA and RNA-based vaccines, and indeed anything that can be delivered using a standardized gene therapy vector. For example, instead of teaching each person's immune system to evolve protective antibodies by showing it pieces of the virus, we can program cells to directly produce known antibodies via gene therapy. Those antibodies could be discovered by sifting existing diverse libraries of hundreds of millions of candidates, computationally designed from scratch, evolved using synthetic laboratory ecosystems, or even harvested from the first patients to report symptoms. Such a vaccine might be discovered and produced fast enough at scale to halt almost any natural pandemic.
Robust production and delivery: Our defenses must not be vulnerable to the social and economic disruptions caused by a pandemic. Unfortunately, our economy selects for speed and efficiency at the expense of robustness. Just-in-time supply chains that wing their way around the world require every node to be intact. If workers aren't on the job producing a critical component, the whole chain breaks until a substitute can be found. A truly nasty pandemic would disrupt economies all over the world, so we will need to pay extra to preserve the capacity for independent vertically integrated production chains in multiple nations. Similarly, vaccines are only useful if people receive them, so delivery systems should be as robustly automated as possible.
None of these defenses will be cheap, but they'll be worth every penny. Our nations collectively spend trillions on defense against one another, but only billions to protect humanity from pandemic viruses known to have killed more people than any human weapon. That's foolish – especially since natural animal diseases that jump the species barrier aren't the only pandemic threats.
We will eventually make our society immune to naturally occurring pandemics, but that day has not yet come, and future pandemic viruses may not be natural.
The complete genomes of all historical pandemic viruses ever to have been sequenced are freely available to anyone with an internet connection. True, these are all agents we've faced before, so we have a pre-existing armory of pharmaceuticals and vaccines and experience. There's no guarantee that they would become pandemics again; for example, a large fraction of humanity is almost certainly immune to the 1918 influenza virus due to exposure to the related 2009 pandemic, making it highly unlikely that the virus would take off if released.
Still, making the blueprints publicly available means that a large and growing number of people with the relevant technical skills can single-handedly make deadly biological agents that might be able to spread autonomously -- at least if they can get their hands on the relevant DNA. At present, such people most certainly can, so long as they bother to check the publicly available list of which gene synthesis companies do the right thing and screen orders -- and by implication, which ones don't.
One would hope that at least some of the companies that don't advertise that they screen are "honeypots" paid by intelligence agencies to catch would-be bioterrorists, but even if most of them are, it's still foolish to let individuals access that kind of destructive power. We will eventually make our society immune to naturally occurring pandemics, but that day has not yet come, and future pandemic viruses may not be natural. Hence, we should build a secure and adaptive system capable of screening all DNA synthesis for known and potential future pandemic agents... without disclosing what we think is a credible bioweapon.
Whether or not it becomes a global pandemic, the emergence of Wuhan coronavirus has underscored the need for coordinated action to prevent the spread of pandemic disease. Let's ensure that our reactive response minimally prepares us for future threats, for one day, reacting may not be enough.