COVID Variants Are Like “a Thief Changing Clothes” – and Our Camera System Barely Exists
Being able to track variants of concern in real time is crucial to our ability to stay ahead of the virus.
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 Only Hydroxychloroquine Story You Need to Read
Hydroxychloroquine has been shown not to provide benefit for COVID-19 patients in multiple randomized controlled trials, despite continuous misinformation asserting its alleged effectiveness.
In the early days of a pandemic caused by a virus with no existing treatments, many different compounds are often considered and tried in an attempt to help patients.
It all relates back to a profound question: How do we know what we know?
Many of these treatments fall by the wayside as evidence accumulates regarding actual efficacy. At that point, other treatments become standard of care once their benefit is proven in rigorously designed trials.
However, about seven months into the pandemic, we're still seeing political resurrection of a treatment that has been systematically studied and demonstrated in well-designed randomized controlled trials to not have benefit.
The hydroxychloroquine (and by extension chloroquine) story is a complicated one that was difficult to follow even before it became infused with politics. It is a simple fact that these drugs, long approved by the Food and Drug Administration (FDA), work in Petri dishes against various viruses including coronaviruses. This set of facts provided biological plausibility to support formally studying their use in the clinical treatment and prevention of COVID-19. As evidence from these studies accumulates, it is a cognitive requirement to integrate that knowledge and not to evade it. This also means evaluating the rigor of the studies.
In recent days we have seen groups yet again promoting the use of hydroxychloroquine in, what is to me, a baffling disregard of the multiple recent studies that have shown no benefit. Indeed, though FDA-approved for other indications like autoimmune conditions and preventing malaria, the emergency use authorization for COVID-19 has been rescinded (which means the government cannot stockpile it). Still, however, many patients continue to ask for the drug, compelled by political commentary, viral videos, and anecdotal data. Yet most doctors (like myself) are refusing to write the prescriptions outside of a clinical trial – a position endorsed by professional medical organizations such as the American College of Physicians and the Infectious Diseases Society of America. Why this disconnect?
It all relates back to a profound question: How do we know what we know? In science, we use the scientific method – the process of observing reality, coming up with a hypothesis about what might be true, and testing that hypothesis as thoroughly as possible until we discover the objective truth.
The confusion we're seeing now stems from an inability to distinguish between anecdotes reported by physicians (observational data) and an actual evidence base. This is understandable among the general public but when done by a healthcare professional, it reveals a disdain for reason, logic, and the scientific method.
The Difference Between Observational Data and Randomized Controlled Trials
The power of informal observation is crucial. It is part of the scientific method but primarily as a basis for generating hypotheses that we can test. How do we conduct medical tests? The gold standard is the double-blind, randomized, placebo-controlled trial. This means that neither the researchers nor the volunteers know who is getting a drug and who is getting a sugar pill. Then both groups of the trial, called arms, can be compared to determine whether the people who got the drug fared better. This study design prevents biases and the placebo effect from confounding the data and undermining the veracity of the results.
For example, a seemingly beneficial effect might be seen in an observational study with no blinding and no control group. In such a case, all patients are openly given the drug and their doctors observe how they do. A prime example is the 36-patient single-arm study from France that generated a tremendous amount of interest after President Trump tweeted about it. But this kind of a study by its nature cannot answer the critical question: Was the positive effect because of hydroxychloroquine or just the natural course of the illness? In other words, would someone have recovered in a similar fashion regardless of the drug? What is the role of the placebo effect?
These are reasons why it is crucial to give a placebo to a control group that is as similar in every respect as possible to those receiving the intervention. Then we attempt to find out by comparing the two groups: What is the side effect profile of the drug? Are the groups large enough to detect a relatively rare safety concern? How long were the patients followed for? Was something else responsible for making the patients get better, such as the use of steroids (as likely was the case in the Henry Ford study)?
Looking at the two major hydroxychloroquine trials, it is apparent that, when studied using the best tools of clinical trials, no benefit is likely to occur.
All of these considerations amount to just a fraction of the questions that can be answered more definitively in a well-designed large randomized controlled trial than in observational studies. Indeed, an observational study from New York failed to show any benefit in hospitalized patients, showing how unclear and disparate the results can be with these types of studies. A New York retrospective study (which examined patient outcomes after they were already treated) had similar results and included the use of azithromycin.
When evaluating a study, it is also important to note whether conflicts of interest exist, as well as the quality of the peer review and the data itself. In the case of the French study, for example, the paper was published in a journal in which one of the authors was editor-in-chief, and it was accepted for publication after 24 hours. Patients who fared poorly on hydroxychloroquine were also left out of the study altogether, skewing the results.
What Randomized Controlled Trials Have Shown
Looking at the two major hydroxychloroquine trials, it is apparent that, when studied using the best tools of clinical trials, no benefit is likely to occur. The most important of these studies to announce results was part of the Recovery trial, which was designed to test multiple interventions in the treatment of COVID-19. This trial, which has yet to be formally published, was a randomized controlled trial that involved over 1500 hospitalized patients being administered hydroxychloroquine compared to over 3000 who did not receive the medication. Clinical testing requires large numbers of patients to have the power to demonstrate statistical significance -- the threshold at which any apparent benefit is more than you would expect by random chance alone.
In this study, hydroxychloroquine provided no mortality benefit or even a benefit in hospital length of stay. In fact, the opposite occurred. Hydroxychloroquine patients were more likely to stay in the hospital longer and were more likely to require mechanical ventilation. Additionally, smaller randomized trials conducted in China have not shown benefit either.
Another major study involved the use of hydroxychloroquine to prevent illness in people who were exposed to COVID-19. These results, published in The New England Journal of Medicine, included over 800 patients who were studied in a randomized double-blind controlled trial and also failed to show any benefit.
But what about adding the antibiotic azithromycin in conjunction with hydroxychloroquine? A three-arm randomized controlled study involving over 500 patients hospitalized with mild to moderate COVID-19 was conducted. Its results, also published in The New England Journal of Medicine, failed to show any benefit – with or without azithromycin – and demonstrated evidence of harm. Those who received these treatments had elevations of their liver function tests and heart rhythm abnormalities. These findings hold despite the retraction of an observational study showing similar results.
Additionally, when used in combination with remdesivir – an experimental antiviral – hydroxychloroquine has been shown to be associated with worse outcomes and more side effects.
But what about in mildly ill patients not requiring hospitalization? There was no benefit found in a randomized double-blind placebo-controlled trial of 400 patients, the majority of whom were given the drug within one day of symptoms.
Some randomized controlled studies have yet to report their findings on hydroxychloroquine in non-hospitalized patients, with the use of zinc (which has some evidence in the treatment of the common cold, another ailment that can be caused by coronaviruses). And studies have yet to come out regarding whether hydroxychloroquine can prevent people from getting sick before they are even exposed. But the preponderance of the evidence from studies designed specifically to find benefit for treating COVID-19 does not support its use outside of a research setting.
Today – even with some studies (including those with zinc) still ongoing – if a patient asked me to prescribe them hydroxychloroquine for any severity or stage of illness, with or without zinc, with or without azithromycin, I would refrain. I would explain that, based on the evidence from clinical trials that has been amassed, there is no reason to believe that it will alter the course of illness for the better.
Failing to recognize the reality of the situation runs the risk of crowding out other more promising treatments and creating animosity where none should exist.
What has been occurring is a continual shifting of goalposts with each negative hydroxychloroquine study. Those in favor of the drug protest that a trial did not include azithromycin or zinc or wasn't given at the right time to the right patients. While there may be biological plausibility to treating illness early or combining treatments with zinc, it can only be definitively shown in a randomized, controlled prospective study.
The bottom line: A study that only looks at past outcomes in one group of patients – even when well conducted – is at most hypothesis generating and cannot be used as the sole basis for a new treatment paradigm.
Some may argue that there is no time to wait for definitive studies, but no treatment is benign. The risk/benefit ratio is not the same for every possible use of the drug. For example, hydroxychloroquine has a long record of use in rheumatoid arthritis and systemic lupus (whose patients are facing shortages because of COVID-19 related demand). But the risk of side effects for many of these patients is worth taking because of the substantial benefit the drug provides in treating those conditions.
In COVID-19, however, the disease apparently causes cardiac abnormalities in a great deal of many mild cases, a situation that should prompt caution when using any drugs that have known effects on the cardiac system -- drugs like hydroxychloroquine and azithromycin.
My Own Experience
It is not the case that every physician was biased against this drug from the start. Indeed, most of us wanted it to be shown to be beneficial, as it was a generic drug that was widely available and very familiar. In fact, early in the pandemic I prescribed it to hospitalized patients on two occasions per a hospital protocol. However, it is impossible for me as a sole clinician to know whether it worked, was neutral, or was harmful. In recent days, however, I have found the hydroxychloroquine talk to have polluted the atmosphere. One recent patient was initially refusing remdesivir, a drug proven in large randomized trials to have effectiveness, because he had confused it with hydroxychloroquine.
Moving On to Other COVID Treatments: What a Treatment Should Do
The story of hydroxychloroquine illustrates a fruitless search for what we are actually looking for in a COVID-19 treatment. In short, we are looking for a medication that can decrease symptoms, decrease complications, hasten recovery, decrease hospitalizations, decrease contagiousness, decrease deaths, and prevent infection. While it is unlikely to find a single antiviral that can accomplish all of these, fulfilling even just one is important.
For example, remdesivir hastens recovery and dexamethasone decreases mortality. Definitive results of the use of convalescent plasma and immunomodulating drugs such as siltuxamab, baricitinib, and anakinra (for use in the cytokine storms characteristic of severe disease) are still pending, as are the trials with monoclonal antibodies.
While it was crucial that the medical and scientific community definitively answer the questions surrounding the use of chloroquine and hydroxychloroquine in the treatment of COVID-19, it is time to face the facts and accept that its use for the treatment of this disease is not likely to be beneficial. Failing to recognize the reality of the situation runs the risk of crowding out other more promising treatments and creating animosity where none should exist.
Dr. Adalja is focused on emerging infectious disease, pandemic preparedness, and biosecurity. He has served on US government panels tasked with developing guidelines for the treatment of plague, botulism, and anthrax in mass casualty settings and the system of care for infectious disease emergencies, and as an external advisor to the New York City Health and Hospital Emergency Management Highly Infectious Disease training program, as well as on a FEMA working group on nuclear disaster recovery. Dr. Adalja is an Associate Editor of the journal Health Security. He was a coeditor of the volume Global Catastrophic Biological Risks, a contributing author for the Handbook of Bioterrorism and Disaster Medicine, the Emergency Medicine CorePendium, Clinical Microbiology Made Ridiculously Simple, UpToDate's section on biological terrorism, and a NATO volume on bioterrorism. He has also published in such journals as the New England Journal of Medicine, the Journal of Infectious Diseases, Clinical Infectious Diseases, Emerging Infectious Diseases, and the Annals of Emergency Medicine. He is a board-certified physician in internal medicine, emergency medicine, infectious diseases, and critical care medicine. Follow him on Twitter: @AmeshAA
Drugs That Trick Older People’s Bodies to Behave Younger Might Boost the Effectiveness of a COVID-19 Vaccine
Because vaccination may be less effective in older people, it is imperative to test now whether immune boosters could help the efficacy of a COVID-19 vaccine in the elderly.
In our April 23rd editorial for this magazine, we argued that addressing the COVID-19 pandemic requires that we both fight the SARS-CoV-2 virus and fortify the human hosts who are most vulnerable to it.
Two recent phase 2 studies in older adults have suggested that a new category of drugs called rapalogues can in some cases increase the immunization capacity of older adults.
Because people over 70 account for more than 80 percent of reported COVID-19 deaths globally, this means we must do everything possible to protect our elders.
A range of recent studies have suggested that systemic knobs might metaphorically be turned to slow the cellular aging process, making us better able to fight off the many diseases correlated with aging. These types of systemic changes might be used to stem the specific decline in immunity caused by aging and to increases the biological capacity of elderly people to effectively fight viral infection.
But while helping make older people more resilient in the face of a viral infection is critical, that's not the only way geroscience can help in our fight against this deadly pandemic.
As we move toward hopefully developing one or more COVID-19 vaccines, researchers must more fully appreciate the ways in which traditional vaccines can be less effective in older people than in younger ones.
Repeated studies have shown that the flu vaccine, for example, has lower efficacy in older people than in younger ones. Older people tend to develop fewer antibodies after being vaccinated because a subset of their white blood cells, called T cells, have become less responsive over time. Some inflammatory peptides that increase with aging are also preventing the action of those T cells.
This is why there's a distinct possibility that a future COVD-19 vaccine, particularly one utilizing the traditional attenuated virus approach, could be less effective in older people than in younger ones.
Given the extreme urgency of developing vaccines that work well for everyone, we need to make sure that researchers are exploring all of the ways our elders can be best protected. While generating a vaccine that works equally well for people of all ages would be ideal, we can't count on that.
One way to bridge this gap might be to trick the bodies of older people into behaving as if they are younger just at the moment what a vaccine is delivered by giving them pre-immunization boosters.
Two recent phase 2 studies in older adults have suggested that a new category of drugs called rapalogues can in some cases increase the immunization capacity of older adults. Use of the drug for a short time period before flu shot immunization increased the antibody production for the flu and resulted in a 52 percent decrease in the occurrence of severe diseases needing medical help or hospitalization. This short-term pre-immunization intervention can also decrease the severity of serious respiratory tract infections, the deadliest manifestations of COVID-19, by similar magnitude. These patients also had almost half the incidence of the non-COVID-19 coronaviruses associated with the common cold.
The fact that those people were protected by treatment before hospitalization suggests metformin may have a role in boosting the vaccination of older people.
An inexpensive generic drug called metformin similarly targets the decline in immunity and inflammation (and extends health span and lifespan) in animals and has been used for decades to protect against the flu. A recent paper from a hospital in Wuhan, China showed that mortality of elderly COVID-19 diabetic patients on metformin was 25 percent less than that of patients with diabetes but not on metformin.
Another study from the U.S. showed that COVID-19 patients on metformin had a 20 percent decrease in mortality and lower inflammation. The fact that those people were protected by treatment before hospitalization suggests metformin may have a role in boosting the vaccination of older people.
We don't yet know whether rapalogues or metformin could be used as COVID-19 immunization boosters, not least because we don't have those vaccines. But we can and should make sure that all vaccine trials including older subjects also consider offering a subset of those subjects appropriate doses of rapalogues or metformin to explore whether doing so can boost the efficacy of a given vaccine.
If we weren't in the middle of the worst pandemic in a century, we would have more time to test our vaccines slowly and sequentially. In the context of the current crisis, however, testing whether immunization boosters might increase the efficacy of potential COVID-19 vaccines for older adults is at the very least a hypothesis worth exploring.