What to Know about the Fast-Spreading Delta Variant
A highly contagious form of the coronavirus known as the Delta variant is spreading rapidly and becoming increasingly prevalent around the world. First identified in India in December, Delta has now been identified in 111 countries.
In the United States, the variant now accounts for 83% of sequenced COVID-19 cases, said Rochelle Walensky, director of the Centers for Disease Control and Prevention, at a July 20 Senate hearing. In May, Delta was responsible for just 3% of U.S. cases. The World Health Organization projects that Delta will become the dominant variant globally over the coming months.
So, how worried should you be about the Delta variant? We asked experts some common questions about Delta.
What is a variant?
To understand Delta, it's helpful to first understand what a variant is. When a virus infects a person, it gets into your cells and makes a copy of its genome so it can replicate and spread throughout your body.
In the process of making new copies of itself, the virus can make a mistake in its genetic code. Because viruses are replicating all the time, these mistakes — also called mutations — happen pretty often. A new variant emerges when a virus acquires one or more new mutations and starts spreading within a population.
There are thousands of SARS-CoV-2 variants, but most of them don't substantially change the way the virus behaves. The variants that scientists are most interested in are known as variants of concern. These are versions of the virus with mutations that allow the virus to spread more easily, evade vaccines, or cause more severe disease.
"The vast majority of the mutations that have accumulated in SARS-CoV-2 don't change the biology as far as we're concerned," said Jennifer Surtees, a biochemist at the University of Buffalo who's studying the coronavirus. "But there have been a handful of key mutations and combinations of mutations that have led to what we're now calling variants of concern."
One of those variants of concern is Delta, which is now driving many new COVID-19 infections.
Why is the Delta variant so concerning?
"The reason why the Delta variant is concerning is because it's causing an increase in transmission," said Alba Grifoni, an infectious disease researcher at the La Jolla Institute for Immunology. "The virus is spreading faster and people — particularly those who are not vaccinated yet — are more prone to exposure."
The Delta variant has a few key mutations that make it better at attaching to our cells and evading the neutralizing antibodies in our immune system. These mutations have changed the virus enough to make it more than twice as contagious as the original SARS-CoV-2 virus that emerged in Wuhan and about 50% more contagious than the Alpha variant, previously known as B.1.1.7, or the U.K. variant.
These mutations were previously seen in other variants on their own, but it's their combination that makes Delta so much more infectious.
Do vaccines work against the Delta variant?
The good news is, the COVID-19 vaccines made by AstraZeneca, Johnson & Johnson, Moderna, and Pfizer still work against the Delta variant. They remain more than 90% effective at preventing hospitalizations and death due to Delta. While they're slightly less protective against disease symptoms, they're still very effective at preventing severe illness caused by the Delta variant.
"They're not as good as they were against the prior strains, but they're holding up pretty well," said Eric Topol, a physician and director of the Scripps Translational Research Institute, during a July 19 briefing for journalists.
Because Delta is better at evading our immune systems, it's likely causing more breakthrough infections — COVID-19 cases in people who are vaccinated. However, breakthrough infections were expected before the Delta variant became widespread. No vaccine is 100% effective, so breakthrough infections can happen with other vaccines as well. Experts say the COVID-19 vaccines are still working as expected, even if breakthrough infections occur. The majority of these infections are asymptomatic or cause only mild symptoms.
Should vaccinated people worry about the Delta variant?
Vaccines train our immune systems to protect us against infection. They do this by spurring the production of antibodies, which stick around in our bodies to help fight off a particular pathogen in case we ever come into contact with it.
But even if the new Delta variant slips past our neutralizing antibodies, there's another component of our immune system that can help overtake the virus: T cells. Studies are showing that the COVID-19 vaccines also galvanize T cells, which help limit disease severity in people who have been vaccinated.
"While antibodies block the virus and prevent the virus from infecting cells, T cells are able to attack cells that have already been infected," Grifoni said. In other words, T cells can prevent the infection from spreading to more places in the body. A study published July 1 by Grifoni and her colleagues found that T cells were still able to recognize mutated forms of the virus — further evidence that our current vaccines are effective against Delta.
Can fully vaccinated people spread the Delta variant?
Previously, scientists believed it was unlikely for fully vaccinated individuals with asymptomatic infections to spread Covid-19. But the Delta variant causes the virus to make so many more copies of itself inside the body, and high viral loads have been found in the respiratory tracts of people who are fully vaccinated. This suggests that vaccinated people may be able to spread the Delta variant to some degree.
If you have COVID-19 symptoms, even if you're fully vaccinated, you should get tested and isolate from friends and family because you could spread the virus.
What risk does Delta pose to unvaccinated people?
The Delta variant is behind a surge in cases in communities with low vaccination rates, and unvaccinated Americans currently account for 97% of hospitalizations due to COVID-19, according to Walensky. The best thing you can do right now to prevent yourself from getting sick is to get vaccinated.
Gigi Gronvall, an immunologist and senior scholar at the Johns Hopkins Center for Health Security, said in this week's "Making Sense of Science" podcast that it's especially important to get all required doses of the vaccine in order to have the best protection against the Delta variant. "Even if it's been more than the allotted time that you were told to come back and get the second, there's no time like the present," she said.
With more than 3.6 billion COVID-19 doses administered globally, the vaccines have been shown to be incredibly safe. Serious adverse effects are rare, although scientists continue to monitor for them.
Being vaccinated also helps prevent the emergence of new and potentially more dangerous variants. Viruses need to infect people in order to replicate, and variants emerge because the virus continues to infect more people. More infections create more opportunities for the virus to acquire new mutations.
Surtees and others worry about a scenario in which a new variant emerges that's even more transmissible or resistant to vaccines. "This is our window of opportunity to try to get as many people vaccinated as possible and get people protected so that so that the virus doesn't evolve to be even better at infecting people," she said.
Does Delta cause more severe disease?
While hospitalizations and deaths from COVID-19 are increasing again, it's not yet clear whether Delta causes more severe illness than previous strains.
How can we protect unvaccinated children from the Delta variant?
With children 12 and under not yet eligible for the COVID-19 vaccine, kids are especially vulnerable to the Delta variant. One way to protect unvaccinated children is for parents and other close family members to get vaccinated.
It's also a good idea to keep masks handy when going out in public places. Due to risk Delta poses, the American Academy of Pediatrics issued new guidelines July 19 recommending that all staff and students over age 2 wear face masks in school this fall, even if they have been vaccinated.
Parents should also avoid taking their unvaccinated children to crowded, indoor locations and make sure their kids are practicing good hand-washing hygiene. For children younger than 2, limit visits with friends and family members who are unvaccinated or whose vaccination status is unknown and keep up social distancing practices while in public.
While there's no evidence yet that Delta increases disease severity in children, parents should be mindful that in some rare cases, kids can get a severe form of the disease.
"We're seeing more children getting sick and we're seeing some of them get very sick," Surtees said. "Those children can then pass on the virus to other individuals, including people who are immunocompromised or unvaccinated."
The Case for an Outright Ban on Facial Recognition Technology
[Editor's Note: This essay is in response to our current Big Question, which we posed to experts with different perspectives: "Do you think the use of facial recognition technology by the police or government should be banned? If so, why? If not, what limits, if any, should be placed on its use?"]
In a surprise appearance at the tail end of Amazon's much-hyped annual product event last month, CEO Jeff Bezos casually told reporters that his company is writing its own facial recognition legislation.
The use of computer algorithms to analyze massive databases of footage and photographs could render human privacy extinct.
It seems that when you're the wealthiest human alive, there's nothing strange about your company––the largest in the world profiting from the spread of face surveillance technology––writing the rules that govern it.
But if lawmakers and advocates fall into Silicon Valley's trap of "regulating" facial recognition and other forms of invasive biometric surveillance, that's exactly what will happen.
Industry-friendly regulations won't fix the dangers inherent in widespread use of face scanning software, whether it's deployed by governments or for commercial purposes. The use of this technology in public places and for surveillance purposes should be banned outright, and its use by private companies and individuals should be severely restricted. As artificial intelligence expert Luke Stark wrote, it's dangerous enough that it should be outlawed for "almost all practical purposes."
Like biological or nuclear weapons, facial recognition poses such a profound threat to the future of humanity and our basic rights that any potential benefits are far outweighed by the inevitable harms.
We live in cities and towns with an exponentially growing number of always-on cameras, installed in everything from cars to children's toys to Amazon's police-friendly doorbells. The use of computer algorithms to analyze massive databases of footage and photographs could render human privacy extinct. It's a world where nearly everything we do, everywhere we go, everyone we associate with, and everything we buy — or look at and even think of buying — is recorded and can be tracked and analyzed at a mass scale for unimaginably awful purposes.
Biometric tracking enables the automated and pervasive monitoring of an entire population. There's ample evidence that this type of dragnet mass data collection and analysis is not useful for public safety, but it's perfect for oppression and social control.
Law enforcement defenders of facial recognition often state that the technology simply lets them do what they would be doing anyway: compare footage or photos against mug shots, drivers licenses, or other databases, but faster. And they're not wrong. But the speed and automation enabled by artificial intelligence-powered surveillance fundamentally changes the impact of that surveillance on our society. Being able to do something exponentially faster, and using significantly less human and financial resources, alters the nature of that thing. The Fourth Amendment becomes meaningless in a world where private companies record everything we do and provide governments with easy tools to request and analyze footage from a growing, privately owned, panopticon.
Tech giants like Microsoft and Amazon insist that facial recognition will be a lucrative boon for humanity, as long as there are proper safeguards in place. This disingenuous call for regulation is straight out of the same lobbying playbook that telecom companies have used to attack net neutrality and Silicon Valley has used to scuttle meaningful data privacy legislation. Companies are calling for regulation because they want their corporate lawyers and lobbyists to help write the rules of the road, to ensure those rules are friendly to their business models. They're trying to skip the debate about what role, if any, technology this uniquely dangerous should play in a free and open society. They want to rush ahead to the discussion about how we roll it out.
We need spaces that are free from government and societal intrusion in order to advance as a civilization.
Facial recognition is spreading very quickly. But backlash is growing too. Several cities have already banned government entities, including police and schools, from using biometric surveillance. Others have local ordinances in the works, and there's state legislation brewing in Michigan, Massachusetts, Utah, and California. Meanwhile, there is growing bipartisan agreement in U.S. Congress to rein in government use of facial recognition. We've also seen significant backlash to facial recognition growing in the U.K., within the European Parliament, and in Sweden, which recently banned its use in schools following a fine under the General Data Protection Regulation (GDPR).
At least two frontrunners in the 2020 presidential campaign have backed a ban on law enforcement use of facial recognition. Many of the largest music festivals in the world responded to Fight for the Future's campaign and committed to not use facial recognition technology on music fans.
There has been widespread reporting on the fact that existing facial recognition algorithms exhibit systemic racial and gender bias, and are more likely to misidentify people with darker skin, or who are not perceived by a computer to be a white man. Critics are right to highlight this algorithmic bias. Facial recognition is being used by law enforcement in cities like Detroit right now, and the racial bias baked into that software is doing harm. It's exacerbating existing forms of racial profiling and discrimination in everything from public housing to the criminal justice system.
But the companies that make facial recognition assure us this bias is a bug, not a feature, and that they can fix it. And they might be right. Face scanning algorithms for many purposes will improve over time. But facial recognition becoming more accurate doesn't make it less of a threat to human rights. This technology is dangerous when it's broken, but at a mass scale, it's even more dangerous when it works. And it will still disproportionately harm our society's most vulnerable members.
Persistent monitoring and policing of our behavior breeds conformity, benefits tyrants, and enriches elites.
We need spaces that are free from government and societal intrusion in order to advance as a civilization. If technology makes it so that laws can be enforced 100 percent of the time, there is no room to test whether those laws are just. If the U.S. government had ubiquitous facial recognition surveillance 50 years ago when homosexuality was still criminalized, would the LGBTQ rights movement ever have formed? In a world where private spaces don't exist, would people have felt safe enough to leave the closet and gather, build community, and form a movement? Freedom from surveillance is necessary for deviation from social norms as well as to dissent from authority, without which societal progress halts.
Persistent monitoring and policing of our behavior breeds conformity, benefits tyrants, and enriches elites. Drawing a line in the sand around tech-enhanced surveillance is the fundamental fight of this generation. Lining up to get our faces scanned to participate in society doesn't just threaten our privacy, it threatens our humanity, and our ability to be ourselves.
[Editor's Note: Read the opposite perspective here.]
Scientists Are Building an “AccuWeather” for Germs to Predict Your Risk of Getting the Flu
Applied mathematician Sara del Valle works at the U.S.'s foremost nuclear weapons lab: Los Alamos. Once colloquially called Atomic City, it's a hidden place 45 minutes into the mountains northwest of Santa Fe. Here, engineers developed the first atomic bomb.
Like AccuWeather, an app for disease prediction could help people alter their behavior to live better lives.
Today, Los Alamos still a small science town, though no longer a secret, nor in the business of building new bombs. Instead, it's tasked with, among other things, keeping the stockpile of nuclear weapons safe and stable: not exploding when they're not supposed to (yes, please) and exploding if someone presses that red button (please, no).
Del Valle, though, doesn't work on any of that. Los Alamos is also interested in other kinds of booms—like the explosion of a contagious disease that could take down a city. Predicting (and, ideally, preventing) such epidemics is del Valle's passion. She hopes to develop an app that's like AccuWeather for germs: It would tell you your chance of getting the flu, or dengue or Zika, in your city on a given day. And like AccuWeather, it could help people alter their behavior to live better lives, whether that means staying home on a snowy morning or washing their hands on a sickness-heavy commute.
Sara del Valle of Los Alamos is working to predict and prevent epidemics using data and machine learning.
Since the beginning of del Valle's career, she's been driven by one thing: using data and predictions to help people behave practically around pathogens. As a kid, she'd always been good at math, but when she found out she could use it to capture the tentacular spread of disease, and not just manipulate abstractions, she was hooked.
When she made her way to Los Alamos, she started looking at what people were doing during outbreaks. Using social media like Twitter, Google search data, and Wikipedia, the team started to sift for trends. Were people talking about hygiene, like hand-washing? Or about being sick? Were they Googling information about mosquitoes? Searching Wikipedia for symptoms? And how did those things correlate with the spread of disease?
It was a new, faster way to think about how pathogens propagate in the real world. Usually, there's a 10- to 14-day lag in the U.S. between when doctors tap numbers into spreadsheets and when that information becomes public. By then, the world has moved on, and so has the disease—to other villages, other victims.
"We found there was a correlation between actual flu incidents in a community and the number of searches online and the number of tweets online," says del Valle. That was when she first let herself dream about a real-time forecast, not a 10-days-later backcast. Del Valle's group—computer scientists, mathematicians, statisticians, economists, public health professionals, epidemiologists, satellite analysis experts—has continued to work on the problem ever since their first Twitter parsing, in 2011.
They've had their share of outbreaks to track. Looking back at the 2009 swine flu pandemic, they saw people buying face masks and paying attention to the cleanliness of their hands. "People were talking about whether or not they needed to cancel their vacation," she says, and also whether pork products—which have nothing to do with swine flu—were safe to buy.
At the latest meeting with all the prediction groups, del Valle's flu models took first and second place.
They watched internet conversations during the measles outbreak in California. "There's a lot of online discussion about anti-vax sentiment, and people trying to convince people to vaccinate children and vice versa," she says.
Today, they work on predicting the spread of Zika, Chikungunya, and dengue fever, as well as the plain old flu. And according to the CDC, that latter effort is going well.
Since 2015, the CDC has run the Epidemic Prediction Initiative, a competition in which teams like de Valle's submit weekly predictions of how raging the flu will be in particular locations, along with other ailments occasionally. Michael Johannson is co-founder and leader of the program, which began with the Dengue Forecasting Project. Its goal, he says, was to predict when dengue cases would blow up, when previously an area just had a low-level baseline of sick people. "You'll get this massive epidemic where all of a sudden, instead of 3,000 to 4,000 cases, you have 20,000 cases," he says. "They kind of come out of nowhere."
But the "kind of" is key: The outbreaks surely come out of somewhere and, if scientists applied research and data the right way, they could forecast the upswing and perhaps dodge a bomb before it hit big-time. Questions about how big, when, and where are also key to the flu.
A big part of these projects is the CDC giving the right researchers access to the right information, and the structure to both forecast useful public-health outcomes and to compare how well the models are doing. The extra information has been great for the Los Alamos effort. "We don't have to call departments and beg for data," says del Valle.
When data isn't available, "proxies"—things like symptom searches, tweets about empty offices, satellite images showing a green, wet, mosquito-friendly landscape—are helpful: You don't have to rely on anyone's health department.
At the latest meeting with all the prediction groups, del Valle's flu models took first and second place. But del Valle wants more than weekly numbers on a government website; she wants that weather-app-inspired fortune-teller, incorporating the many diseases you could get today, standing right where you are. "That's our dream," she says.
This plot shows the the correlations between the online data stream, from Wikipedia, and various infectious diseases in different countries. The results of del Valle's predictive models are shown in brown, while the actual number of cases or illness rates are shown in blue.
(Courtesy del Valle)
The goal isn't to turn you into a germophobic agoraphobe. It's to make you more aware when you do go out. "If you know it's going to rain today, you're more likely to bring an umbrella," del Valle says. "When you go on vacation, you always look at the weather and make sure you bring the appropriate clothing. If you do the same thing for diseases, you think, 'There's Zika spreading in Sao Paulo, so maybe I should bring even more mosquito repellent and bring more long sleeves and pants.'"
They're not there yet (don't hold your breath, but do stop touching your mouth). She estimates it's at least a decade away, but advances in machine learning could accelerate that hypothetical timeline. "We're doing baby steps," says del Valle, starting with the flu in the U.S., dengue in Brazil, and other efforts in Colombia, Ecuador, and Canada. "Going from there to forecasting all diseases around the globe is a long way," she says.
But even AccuWeather started small: One man began predicting weather for a utility company, then helping ski resorts optimize their snowmaking. His influence snowballed, and now private forecasting apps, including AccuWeather's, populate phones across the planet. The company's progression hasn't been without controversy—privacy incursions, inaccuracy of long-term forecasts, fights with the government—but it has continued, for better and for worse.
Disease apps, perhaps spun out of a small, unlikely team at a nuclear-weapons lab, could grow and breed in a similar way. And both the controversies and public-health benefits that may someday spin out of them lie in the future, impossible to predict with certainty.