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."
Your phone could show if a bridge is about to collapse
In summer 2017, Thomas Matarazzo, then a postdoctoral researcher at the Massachusetts Institute of Technology, landed in San Francisco with a colleague. They rented two cars, drove up to the Golden Gate bridge, timing it to the city’s rush hour, and rode over to the other side in heavy traffic. Once they reached the other end, they turned around and did it again. And again. And again.
“I drove over that bridge 100 times over five days, back and forth,” says Matarazzo, now an associate director of High-Performance Computing in the Center for Innovation in Engineering at the United States Military Academy, West Point. “It was surprisingly stressful, I never anticipated that. I had to maintain the speed of about 30 miles an hour when the speed limit is 45. I felt bad for everybody behind me.”
Matarazzo had to drive slowly because the quality of data they were collecting depended on it. The pair was designing and testing a new smartphone app that could gather data about the bridge’s structural integrity—a low-cost citizen-scientist alternative to the current industrial methods, which aren’t always possible, partly because they’re expensive and complex. In the era of aging infrastructure, when some bridges in the United States and other countries are structurally unsound to the point of collapsing, such an app could inform authorities about the need for urgent repairs, or at least prompt closing the most dangerous structures.
There are 619,588 bridges in the U.S., and some of them are very old. For example, the Benjamin Franklin Bridge connecting Philadelphia to Camden, N.J., is 96-years-old while the Brooklyn Bridge is 153. So it’s hardly surprising that many could use some upgrades. “In the U.S., a lot of them were built in the post-World War II period to accommodate the surge of motorization,” says Carlo Ratti, architect and engineer who directs the Senseable City Lab at Massachusetts Institute of Technology. “They are beginning to reach the end of their life.”
According to the 2022 American Road & Transportation Builders Association’s report, one in three U.S. bridges needs repair or replacement. The Department of Transportation (DOT) National Bridge Inventory (NBI) database reveals concerning numbers. Thirty-six percent of U.S. bridges need repair work and over 78,000 bridges should be replaced. More than 43,500 bridges are rated in poor condition and classified as “structurally deficient” – an alarming description. Yet, people drive over them 167.5 million times a day. The Pittsburgh bridge which collapsed in January this year—only hours before President Biden arrived to discuss the new infrastructure law—was on the “poor” rating list.
Assessing the structural integrity of a bridge is not an easy endeavor. Most of the time, these are visual inspections, Matarazzo explains. Engineers check cracks, rust and other signs of wear and tear. They also check for wildlife—birds which may build nests or even small animals that make homes inside the bridge structures, which can slowly chip at the structure. However, visual inspections may not tell the whole story. A more sophisticated and significantly more expensive inspection requires placing special sensors on the bridge that essentially listen to how the bridge vibrates.
“Some bridges can afford expensive sensors to do the job, but that comes at a very high cost—hundreds of thousands of dollars per bridge per year,” Ratti says.
We may think of bridges as immovable steel and concrete monoliths, but they naturally vibrate, oscillating slightly. That movement can be influenced by the traffic that passes over them, and even by wind. Bridges of different types vibrate differently—some have longer vibrational frequencies and others shorter ones. A good way to visualize this phenomenon is to place a ruler over the edge of a desk and flick it slightly. If the ruler protrudes far off the desk, it will vibrate slowly. But if you shorten the end that hangs off, it will vibrate much faster. It works similarly with bridges, except there are more factors at play, including not only the length, but also the design and the materials used.
The long suspension bridges such as the Golden Gate or Verrazano Narrows, which hang on a series of cables, are more flexible, and their vibration amplitudes are longer. The Golden Gate Bridge can vibrate at 0.106 Hertz, where one Hertz is one oscillation per second. “Think about standing on the bridge for about 10 seconds—that's how long it takes for it to move all the way up and all the way down in one oscillation,” Matarazzo says.
On the contrary, the concrete span bridges that rest on multiple columns like Brooklyn Bridge or Manhattan Bridge, are “stiffer” and have greater vibrational frequencies. A concrete bridge can have a frequency of 10 Hertz, moving 10 times in one second—like that shorter stretch of a ruler.
The special devices that can pick up and record these vibrations over time are called accelerometers. A network of these devices for each bridge can cost $20,000 to $50,000, and more—and require trained personnel to place them. The sensors also must stay on the bridge for some time to establish what’s a healthy vibrational baseline for a given bridge. Maintaining them adds to the cost. “Some bridges can afford expensive sensors to do the job, but that comes at a very high cost—hundreds of thousands of dollars per bridge per year,” Ratti says.
Making sense of the readouts they gather is another challenge, which requires a high level of technical expertise. “You generally need somebody, some type of expert capable of doing the analysis to translate that data into information,” says Matarazzo, which ticks up the price, so doing visual inspections often proves to be a more economical choice for state-level DOTs with tight budgets. “The existing systems work well, but have downsides,” Ratti says. The team thought the old method could use some modernizing.
Smartphones, which are carried by millions of people, contain dozens of sensors, including the accelerometers capable of picking up the bridges’ vibrations. That’s why Matarazzo and his colleague drove over the bridge 100 times—they were trying to pick up enough data. Timing it to rush hour supported that goal because traffic caused more “excitation,” Matarazzo explains. “Excitation is a big word we use when we talk about what drives the vibration,” he says. “When there's a lot of traffic, there's more excitation and more vibration.” They also collaborated with Uber, whose drivers made 72 trips across the bridge to gather data in different cars.
The next step was to clean the data from “noise”—various vibrations that weren’t relevant to the bridge but came from the cars themselves. “It could be jumps in speed, it could be potholes, it could be a bunch of other things," Matarazzo says. But as the team gathered more data, it became easier to tell the bridge vibrational frequencies from all others because the noises generated by cars, traffic and other things tend to “cancel out.”
The team specifically picked the Golden Gate bridge because the civil structural engineering community had studied it extensively over the years and collected a host of vibrational data, using traditional sensors. When the researchers compared their app-collected frequencies with those gathered by 240 accelerometers formerly placed on the Golden Gate, the results were the same—the data from the phones converged with that from the bridge’s sensors. The smartphone-collected data were just as good as those from industry devices.
The study authors estimate that officials could use crowdsourced data to make key improvements that would help new bridges to last about 14 years longer.
The team also tested their method on a different type of bridge—not a suspension one like the Golden Gate, but a concrete span bridge in Ciampino, Italy. There they compared 280 car trips over the bridge to the six sensors that had been placed on the bridge for seven months. The results were slightly less matching, but a larger volume of trips would fix the divergence, the researchers wrote in their study, titled Crowdsourcing bridge dynamic monitoring with smartphone vehicle trips, published last month in Nature Communications Engineering.
Although the smartphones proved effective, the app is not quite ready to be rolled out commercially for people to start using. “It is still a pilot version,” so there’s room for improvement, says Ratti, who co-authored the study. “But on a more optimistic note, it has really low barriers to entry—all you need is smartphones on cars—so that makes the system easy to reach a global audience.” And the study authors estimate that the use of crowdsourced data would result in a new bridge lasting about 14 years longer.
Matarazzo hopes that the app could be eventually accessible for your average citizen scientist to collect the data and supply it to their local transportation authorities. “I hope that this idea can spark a different type of relationship with infrastructure where people think about the data they're collecting as some type of contribution or investment into their communities,” he says. “So that they can help their own department of transportation, their own municipality to support that bridge and keep it maintained better, longer and safer.”
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
The Friday Five: Sugar could help catch cancer early
The Friday Five covers five stories in research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
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Here are the promising studies covered in this week's Friday Five:
- Catching cancer early could depend on sugar
- How to boost memory in a flash
- This is your brain on books
- A tiny sandwich cake could help the heart
- Meet the top banana for fighting Covid variants