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."
Democratize the White Coat by Honoring Black, Indigenous, and People of Color in Science
This article is part of the magazine, "The Future of Science In America: The Election Issue," co-published by LeapsMag, the Aspen Institute Science & Society Program, and GOOD.
Journalists, educators, and curators have responded to Black Lives Matter by highlighting the history and achievements of Black Americans in a variety of fields, including science. The movement has also sparked important demands to address longstanding scientific inequities such as lack of access to quality healthcare and the disproportionate impact of climate change and environmental pollution on neighborhoods of Black, Indigenous, and people of color (BIPOC). Making such improvements requires bringing BIPOC into science and into positions of leadership in laboratories, graduate schools, medical practices, and clinical trials. The moment is right to challenge scientific gatekeepers to respond to Black Lives Matter by widening the pathways that determine who becomes a scientist, a researcher, or a clinician.
The scientific workforce has long lacked diversity, which in turn discourages Black people from pursuing such careers. Causes include a dearth of mentors and role models, preconceived notions that science is exclusive to white males, and subpar STEM education. Across race, gender, class, ability, and all other dimensions that inform how an individual navigates the world, from the familial to the global level, seeing role models who resemble you impacts what you strive for and believe possible. As Marian Wright Edelman stated, "You can't be what you can't see"—a truth with ever-increasing resonance since the U.S. is projected to be minority-white by 2045.
Black Americans have paved the way for the nation to lead in science and technology, despite marginalization and exclusion from textbooks. Physicist Dr. Shirley Ann Jackson invented the technology behind Caller I.D. and Call Waiting. Otis Boykin's patents made televisions and radios what they are today. Thanks to the 2017 movie Hidden Figures, millions of Americans know about Katherine Johnson, the NASA mathematician whose calculations were essential to the successful trajectory of the Apollo 11 mission.
However, highlighting past role models who were Black achievers is not enough and paints too static a picture—especially when examples of transformative work by contemporary BIPOC scientists serving BIPOC communities abound. Cognitive neuroscientist Dr. Jonathan Jackson founded the Community Access, Recruitment, & Engagement (CARE) Research Center with the goal to break down barriers so that people of color participate in clinical trials. Geneticist Dr. Nanibaa' Garrison's research creates ethical frameworks to overcome genomic injustices so Indigenous populations can benefit from genetic research. Computer scientists Joy Buolamwini and Dr. Timnit Gebru's research drew attention to reinforced racial bias in artificial intelligence, leading Microsoft, Amazon, and IBM this summer to halt use of their facial recognition software.
"Integration does not mean equality if the space being integrated isn't exuberantly down for the cause."
In order to honor concretely the ubiquitous public statements and commitments to justice and equity that flooded everyone's inboxes in early June, we must include traditionally underrepresented voices in all phases of science and its applications. For guidance, we would benefit from listening to activists leading, for example, climate marches and protests over toxic water. Indeed, science is at the core of the issues for which young BIPOC are mobilizing. We need to sit down with these individuals to gain their input on how the narratives, practices, and opportunities in science should change. As Zeena Abdulkarim, a youth climate change organizer working with Zero Hour, explains: "Minority communities are exposed to what the privileged and people in power are not; therefore these communities know the right steps to take in the change we need for the kickstart of true social and environmental justice."
Two other Black youth, for example, used the platform of the laboratory while in high school to mobilize for change. Elle Lanair Lett, now specializing in epidemiology as an M.D.-Ph.D. student in Philadelphia, was prompted by family prevalence of diabetes to research the genetics of pancreatic cells. Dr. Otana Jakpor, now an ophthalmology resident in Michigan, was motivated by the pollution in her hometown of Riverside, California, to research the pulmonary effects of indoor air purifiers, with findings that influenced California ozone regulations. Both became finalists in a national science fair, propelling them on paths toward science careers. These young scientists demonstrate how people's communities and lived experiences can shape trajectories of science research, which, in turn, determines which visions for society are materialized and popularized.
We can also gain insight from another childhood science fair veteran, self-proclaimed "Black STEMinist" Augusta Uwamanzu-Nna, who graduated from college in May and works as a bioengineer. In her view, "we need to shift the burden away from Black people and onto individuals who have contributed to our current reality—fundamentally requiring understanding, open-mindedness, a lack of bias, cultural competency, anti-racism, anti-homophobia, and many, many other things."
Celebrating BIPOC's accomplishments in science and cultivating new leadership today are strong first steps to make science a guiding force for all. Ms. Uwamanzu-Nna keenly reminds us, "Integration does not mean equality if the space being integrated isn't exuberantly down for the cause." Indeed, educational institutions, scientific companies, and medical centers must acknowledge and embrace their role in democratizing science in order for society to realize racial and scientific justice.
[Editor's Note: To read other articles in this special magazine issue, visit the beautifully designed e-reader version.]
This article is part of the magazine, "The Future of Science In America: The Election Issue," co-published by LeapsMag, the Aspen Institute Science & Society Program, and GOOD.
Alethea.ai sports a grid of faces smiling, blinking and looking about. Some are beautiful, some are oddly familiar, but all share one thing in common—they are fake.
Alethea creates "synthetic media"— including digital faces customers can license saying anything they choose with any voice they choose. Companies can hire these photorealistic avatars to appear in explainer videos, advertisements, multimedia projects or any other applications they might dream up without running auditions or paying talent agents or actor fees. Licenses begin at a mere $99. Companies may also license digital avatars of real celebrities or hire mashups created from real celebrities including "Don Exotic" (a mashup of Donald Trump and Joe Exotic) or "Baby Obama" (a large-eared toddler that looks remarkably similar to a former U.S. President).
Naturally, in the midst of the COVID pandemic, the appeal is understandable. Rather than flying to a remote location to film a beer commercial, an actor can simply license their avatar to do the work for them. The question is—where and when this tech will cross the line between legitimately licensed and authorized synthetic media to deep fakes—synthetic videos designed to deceive the public for financial and political gain.
Deep fakes are not new. From written quotes that are manipulated and taken out of context to audio quotes that are spliced together to mean something other than originally intended, misrepresentation has been around for centuries. What is new is the technology that allows this sort of seamless and sophisticated deception to be brought to the world of video.
"At one point, video content was considered more reliable, and had a higher threshold of trust," said Alethea CEO and co-founder, Arif Khan. "We think video is harder to fake and we aren't yet as sensitive to detecting those fakes. But the technology is definitely there."
"In the future, each of us will only trust about 15 people and that's it," said Phil Lelyveld, who serves as Immersive Media Program Lead at the Entertainment Technology Center at the University of Southern California. "It's already very difficult to tell true footage from fake. In the future, I expect this will only become more difficult."
How do we know what's true in a world where original videos created with avatars of celebrities and politicians can be manipulated to say virtually anything?
As the U.S. 2020 Presidential Election nears, the potential moral and ethical implications of this technology are startling. A number of cases of truth tampering have recently been widely publicized. On August 5, President Donald Trump's campaign released an ad featuring several photos of Joe Biden that were altered to make it seem like was hiding all alone in his basement. In one photo, at least ten people who had been sitting with Biden in the original shot were cut out. In other photos, Biden's image was removed from a nature preserve and praying in church to make it appear Biden was in that same basement. Recently several videos of Speaker of the House Nancy Pelosi were slowed down by 75 percent to make her sound as if her speech was slurred.
During a campaign event in Florida on September 15 of this year, former Vice President Joe Biden was introduced by Puerto Rican singer-songwriter Luis Fonsi. After he was introduced, Biden paid tribute to the singer-songwriter—he held up his cell phone and played the hit song "Despecito". Shortly afterward, a doctored version of this video appeared on self-described parody site the United Spot replacing the Despicito with N.W.A.'s "F—- Tha Police". By September 16, Donald Trump retweeted the video, twice—first with the line "What is this all about" and second with the line "China is drooling. They can't believe this!" Twitter was quick to mark the video in these tweets as manipulated media.
Twitter had previously addressed several of Donald Trump's tweets—flagging a video shared in June as manipulated media and removing altogether a video shared by Trump in July showing a group promoting the hydroxychloroquine as an effective cure for COVID-19. Many of these manipulated videos are ultimately flagged or taken down, but not before they are seen and shared by millions of online viewers.
These faked videos were exposed rather quickly, as they could be compared with the original, publicly available source material. But what happens when there is no original source material? How do we know what's true in a world where original videos created with avatars of celebrities and politicians can be manipulated to say virtually anything?
"This type of fake media is a profound threat to our democracy," said Reid Blackman, the CEO of VIRTUE--an ethics consultancy for AI leaders. "Democracy depends on well-informed citizens. When citizens can't or won't discern between real and fake news, the implications are huge."
In light of the importance of reliable information in the political system, there's a clear and present need to verify that the images and news we consume is authentic. So how can anyone ever know that the content they are viewing is real?
"This will not be a simple technological solution," said Blackman. "There is no 'truth' button to push to verify authenticity. There's plenty of blame and condemnation to go around. Purveyors of information have a responsibility to vet the reliability of their sources. And consumers also have a responsibility to vet their sources."
Yet the process of verifying sources has never been more challenging. More and more citizens are choosing to live in a "media bubble"—gathering and sharing news only from and with people who share their political leanings and opinions. At one time, United States broadcasters were bound by the Fairness Doctrine—requiring them to present controversial issues important to the public in a way that the FCC deemed honest, equitable and balanced. The repeal of this doctrine in 1987 paved the way for new forms of cable news channels such as Fox News and MSNBC that appealed to viewers with a particular point of view. The Internet has only exacerbated these tendencies. Social media algorithms are designed to keep people clicking within their comfort zones by presenting members with only the thoughts and opinions they want to hear.
"I sometimes laugh when I hear people tell me they can back a particular opinion they hold with research," said Blackman. "Having conducted a fair bit of true scientific research, I am aware that clicking on one article on the Internet hardly qualifies. But a surprising number of people believe that finding any source online that states the fact they choose to believe is the same as proving it true."
Back to the fundamental challenge: How do we as a society root out what's false online? Lelyveld suggests that it will begin by verifying things that are known to be true rather than trying to call out everything that is fake. "The EU called me in to talk about how to deal with fake news coming out of Russia," said Lelyveld. "I told them Hollywood has spent 100 years developing special effects technology to make things that are wholly fictional indistinguishable from the truth. I told them that you'll never chase down every source of fake news. You're better off focusing on what can be proved true."
Arif Khan agrees. "There are probably 100 accounts attributed to Elon Musk on Twitter, but only one has the blue checkmark," said Khan. "That means Twitter has verified that an account of public interest is real. That's what we're trying to do with our platform. Allow celebrities to verify that specific videos were licensed and authorized directly by them."
Alethea will use another key technology called blockchain to mark all authentic authorized videos with celebrity avatars. Blockchain uses a distributed ledger technology to make sure that no undetected changes have been made to the content. Think of the difference between editing a document in a traditional word processing program and editing in a distributed online editing system like Google Docs. In a traditional word processing program, you can edit and copy a document without revealing any changes. In a shared editing system like Google Docs, every person who shares the document can see a record of every edit, addition and copy made of any portion of the document. In a similar way, blockchain helps Alethea ensure that approved videos have not been copied or altered inappropriately.
While AI companies like Alethea are moving to ensure that avatars based on real individuals aren't wrongly identified, the situation becomes a bit murkier when it comes to the question of representing groups, races, creeds, and other forms of identity. Alethea is rightly proud that the completely artificial avatars visually represent a variety of ages, races and sexes. However, companies could conceivably license an avatar to represent a marginalized group without actually hiring a person within that group to decide what the avatar will do or say.
"I don't know if I would call this tokenism, as that is difficult to identify without understanding the hiring company's intent," said Blackman. "Where this becomes deeply troubling is when avatars are used to represent a marginalized group without clearly pointing out the actor is an avatar. It's one thing for an African American woman avatar to say, 'I like ice cream.' It's entirely different thing for an African American woman avatar to say she supports a particular political candidate. In the second case, the avatar is being used as social proof that real people of a certain type back a certain political idea. And there the deception is far more problematic."
"It always comes down to unintended consequences of technology," said Lelyveld. "Technology is neutral—it's only the implementation that has the power to be good or bad. Without a thoughtful approach to the cultural, moral and political implications of technology, it often drifts towards the bad. We need to make a conscious decision as we release new technology to ensure it moves towards the good."
When presented with the idea that his avatars might be used to misrepresent marginalized groups, Khan was thoughtful. "Yes, I can see that is an unintended consequence of our technology. We would like to encourage people to license the avatars of real people, who would have final approval over what their avatars say or do. As to what people do with our completely artificial avatars, we will have to consider that moving forward."
Lelyveld frankly sees the ability for advertisers to create avatars that are our assistants or even our friends as a greater moral concern. "Once our digital assistant or avatar becomes an integral part of our life—even a friend as it were, what's to stop marketers from having those digital friends make suggestions about what drink we buy, which shirt we wear or even which candidate we elect? The possibilities for bad actors to reach us through our digital circle is mind-boggling."
Ultimately, Blackman suggests, we as a society will need to make decisions about what matters to us. "We will need to build policies and write laws—tackling the biggest problems like political deep fakes first. And then we have to figure out how to make the penalties stiff enough to matter. Fining a multibillion-dollar company a few million for a major offense isn't likely to move the needle. The punishment will need to fit the crime."
Until then, media consumers will need to do their own due diligence—to do the difficult work of uncovering the often messy and deeply uncomfortable news that's the truth.
[Editor's Note: To read other articles in this special magazine issue, visit the beautifully designed e-reader version.]