England is about to take a huge gamble.
On Monday, July 19, the country is ditching all of its remaining pandemic-related restrictions. People will be able to go to nightclubs, or gather in groups as large as they like. They will not be legally compelled to wear masks at all, and can stop social distancing. The government, with an eye on media coverage, has dubbed it “Freedom Day,” and said the lifting of safety measures will be irreversible.
At the same time, coronavirus cases are rapidly rising in the UK. It recorded over 50,000 new cases on Friday, and its health minister says that the daily figure of new infections could climb to over 100,000 over the summer.
In theory, a full reopening during a surge in cases sounds like a combustible mix. But the UK government is betting that this time won’t be like the others because of its vaccination program.
Researchers say it’s extremely difficult to predict what will happen next, with multiple overlapping, complex factors at play. So let’s examine what we know, what we don’t know, and what we need to keep an eye on over the coming weeks.
What we know: the vaccines are working
The UK’s vaccination program is still under way, but it has been broadly successful so far. In all, 52% of the adult population is fully vaccinated, and about 87% of adults have received their first dose (this includes the 52% who have had both doses). Just 6% of Brits are hesitant about getting a shot, according to the Office for National Statistics.
There is still plenty of cause to be nervous, however. The country is months away from fully inoculating the entire adult population. Young people are particularly vulnerable; the over-18s have only just started to receive their first doses, and only a quarter of 18- to 39-year-olds have had both shots. And unlike the US and much of Europe, the UK has not started vaccinating children.
“That’s dangerous,” says evolutionary virologist Emilia Skirmuntt. “We need to vaccinate teenagers urgently, especially before they return to school in September.”
This matters because the overwhelmingly dominant strain of covid-19 in the UK right now is the delta variant. While fully vaccinated people have relatively little reason to worry about delta—with both Pfizer and AstraZeneca vaccines offering over 90% efficacy against hospitalization, according to data from Public Health England—the variant is bad news for those who have only had one shot or are unvaccinated.
It’s about 60% more transmissible than the alpha variant, which was previously dominant in the UK, and almost twice as likely to lead to hospitalization, according to Scotland’s public health body. A single dose of either the AstraZeneca or the Pfizer vaccine is just 33% effective against the delta variant, versus 50% for alpha, says data from Public Health England.
“This reopening is going to lead to a lot of avoidable damage,” says Deepti Gurdasani, a clinical epidemiologist at Queen Mary University of London. “We should be halting easing up until all adults and adolescents have been offered both doses of the vaccine.”
What we don’t know: when cases will peak
It’s clear that the UK is experiencing yet another wave of the pandemic. What we don’t know is just how bad it’s going to get—or how lifting restrictions will change that. Even the top experts in the field can’t say for sure.
“It is very hard to know what is going to happen after July 19,” says Graham Medley, professor of infectious disease modeling at the London School of Hygiene & Tropical Medicine and chair of SPI-M, a group of scientists that advises the UK government on pandemic modeling.
A lot depends on public behavior, and that is notoriously very tricky to predict. While some will enjoy their newfound freedoms with gusto (a tendency that was on full display last weekend during the final of the European soccer championships), others will be far more cautious.
Many people are frustrated at the ditching of masks, one of the most basic and effective public health measures. An Ipsos Mori poll found that a sizable majority of British people plan to continue to wear masks in stores and on public transport. If people follow through on this, it may help curb the spread somewhat: Israel, which also has high vaccination rates, had to reimpose mask-wearing indoors last month in the face of a steep rise in cases.
Regardless, it is very likely that cases will continue to rise for at least a few days, if not a few weeks. And that means more hospitalizations and deaths are inevitable, according to Medley. The big question is how high this wave gets.
In a webinar on Thursday, Chris Whitty, the chief medical officer for England, said the country could see “quite scary numbers again” and “get into trouble again surprisingly fast.”
But the government seems to be betting that not all numbers are equally scary. It hopes that hospitalizations will stay low enough to stop the National Health Service from being completely overwhelmed. It is making the assumption that the link between cases and hospitalization rates has been weakened, if not broken.
“This wave is very different to previous ones,” says Oliver Geffen Obregon, an epidemiologist based in the UK, who has worked with the World Health Organization. “The proportion of hospitalization is way lower compared to similar points on the epidemic curve before the vaccination program.”
But not everyone agrees. NHS bosses are already sounding the alarm over capacity, and more than 1,200 scientists have signed a letter in The Lancet arguing that Britain should care about the huge rise in infections, regardless of the rates of deaths and hospitalizations.
Gurdasani, the epidemiologist, is one of them.
“Cases matter,” she says, pointing to two main dangers: the increased chance that large numbers of people will develop long covid, and the risk of new, vaccine-dodging variants.
What we know: more people will get long covid
The UK already has a significant problem with long covid. More than two million adults may already have—or have had—complications that persist for 12 weeks or more, according to a major study from Imperial College London. But long covid is poorly understood, with over 200 symptoms ranging from fatigue to shortness of breath to memory issues, according to the largest study of it yet, recently published in The Lancet.
About one in 10 of those who catch covid-19 go on to develop long covid, according to the WHO. That means if another million people in the UK get sick during this wave—a plausible scenario by most estimates—there could be another 100,000 people with long-term issues.
Whitty is worried. “I think we will get a significant amount more long covid, particularly in the younger ages where the vaccination rates are currently much lower,” he said on July 6.
That could place huge pressure on the NHS, businesses, and society in general, not to mention causing untold misery for vast numbers of individuals.
“Some symptoms may persist for years, and there’s a chance we’re exposing a whole generation to very bad health for the rest of their lives,” says Skirmuntt.
What we don’t know: whether this could all spawn another dangerous variant
The big fear for many experts is that the government’s approach is creating an ideal breeding ground for the emergence of a vaccine-resistant variant.
On July 5, Steve Paterson, co-director of the Centre for Genomic Research at the University of Liverpool, summed up the concerns in a tweet: “Letting a virus rip through a partially vaccinated population is exactly the experiment I’d do to evolve a virus able to evade immunity.”
Meet the people who warn the world about new covid variants
In March 2020, when the WHO declared a pandemic, the public sequence database GISAID held 524 covid sequences. Over the next month scientists uploaded 6,000 more. By the end of May, the total was over 35,000. (In contrast, global scientists added 40,000 flu sequences to GISAID in all of 2019.)
“Without a name, forget about it—we cannot understand what other people are saying,” says Anderson Brito, a postdoc in genomic epidemiology at the Yale School of Public Health, who contributes to the Pango effort.
As the number of covid sequences spiraled, researchers trying to study them were forced to create entirely new infrastructure and standards on the fly. A universal naming system has been one of the most important elements of this effort: without it, scientists would struggle to talk to each other about how the virus’s descendants are traveling and changing—either to flag up a question or, even more critically, to sound the alarm.
Where Pango came from
In April 2020, a handful of prominent virologists in the UK and Australia proposed a system of letters and numbers for naming lineages, or new branches, of the covid family. It had a logic, and a hierarchy, even though the names it generated—like B.1.1.7—were a bit of a mouthful.
One of the authors on the paper was Áine O’Toole, a PhD candidate at the University of Edinburgh. Soon she’d become the primary person actually doing that sorting and classifying, eventually combing through hundreds of thousands of sequences by hand.
She says: “Very early on, it was just who was available to curate the sequences. That ended up being my job for a good bit. I guess I never understood quite the scale we were going to get to.”
She quickly set about building software to assign new genomes to the right lineages. Not long after that, another researcher, postdoc Emily Scher, built a machine-learning algorithm to speed things up even more.
They named the software Pangolin, a tongue-in-cheek reference to a debate about the animal origin of covid. (The whole system is now simply known as Pango.)
The naming system, along with the software to implement it, quickly became a global essential. Although the WHO has recently started using Greek letters for variants that seem especially concerning, like delta, those nicknames are for the public and the media. Delta actually refers to a growing family of variants, which scientists call by their more precise Pango names: B.1.617.2, AY.1, AY.2, and AY.3.
“When alpha emerged in the UK, Pango made it very easy for us to look for those mutations in our genomes to see if we had that lineage in our country too,” says Jolly. “Ever since then, Pango has been used as the baseline for reporting and surveillance of variants in India.”
Because Pango offers a rational, orderly approach to what would otherwise be chaos, it may forever change the way scientists name viral strains—allowing experts from all over the world to work together with a shared vocabulary. Brito says: “Most likely, this will be a format we’ll use for tracking any other new virus.”
Many of the foundational tools for tracking covid genomes have been developed and maintained by early-career scientists like O’Toole and Scher over the last year and a half. As the need for worldwide covid collaboration exploded, scientists rushed to support it with ad hoc infrastructure like Pango. Much of that work fell to tech-savvy young researchers in their 20s and 30s. They used informal networks and tools that were open source—meaning they were free to use, and anyone could volunteer to add tweaks and improvements.
“The people on the cutting edge of new technologies tend to be grad students and postdocs,” says Angie Hinrichs, a bioinformatician at UC Santa Cruz who joined the project earlier this year. For example, O’Toole and Scher work in the lab of Andrew Rambaut, a genomic epidemiologist who posted the first public covid sequences online after receiving them from Chinese scientists. “They just happened to be perfectly placed to provide these tools that became absolutely critical,” Hinrichs says.
It hasn’t been easy. For most of 2020, O’Toole took on the bulk of the responsibility for identifying and naming new lineages by herself. The university was shuttered, but she and another of Rambaut’s PhD students, Verity Hill, got permission to come into the office. Her commute, walking 40 minutes to school from the apartment where she lived alone, gave her some sense of normalcy.
Every few weeks, O’Toole would download the entire covid repository from the GISAID database, which had grown exponentially each time. Then she would hunt around for groups of genomes with mutations that looked similar, or things that looked odd and might have been mislabeled.
When she got particularly stuck, Hill, Rambaut, and other members of the lab would pitch in to discuss the designations. But the grunt work fell on her.
Deciding when descendants of the virus deserve a new family name can be as much art as science. It was a painstaking process, sifting through an unheard-of number of genomes and asking time and again: Is this a new variant of covid or not?
“It was pretty tedious,” she says. “But it was always really humbling. Imagine going through 20,000 sequences from 100 different places in the world. I saw sequences from places I’d never even heard of.”
As time went on, O’Toole struggled to keep up with the volume of new genomes to sort and name.
In June 2020, there were over 57,000 sequences stored in the GISAID database, and O’Toole had sorted them into 39 variants. By November 2020, a month after she was supposed to turn in her thesis, O’Toole took her last solo run through the data. It took her 10 days to go through all the sequences, which by then numbered 200,000. (Although covid has overshadowed her research on other viruses, she’s putting a chapter on Pango in her thesis.)
Fortunately, the Pango software is built to be collaborative, and others have stepped up. An online community—the one that Jolly turned to when she noticed the variant sweeping across India—sprouted and grew. This year, O’Toole’s work has been much more hands-off. New lineages are now designated mostly when epidemiologists around the world contact O’Toole and the rest of the team through Twitter, email, or GitHub— her preferred method.
“Now it’s more reactionary,” says O’Toole. “If a group of researchers somewhere in the world is working on some data and they believe they’ve identified a new lineage, they can put in a request.”
The deluge of data has continued. This past spring, the team held a “pangothon,” a sort of hackathon in which they sorted 800,000 sequences into around 1,200 lineages.
“We gave ourselves three solid days,” says O’Toole. “It took two weeks.”
Since then, the Pango team has recruited a few more volunteers, like UCSC researcher Hindriks and Yale researcher Brito, who both got involved initially by adding their two cents on Twitter and the GitHub page. A postdoc at the University of Cambridge, Chris Ruis, has turned his attention to helping O’Toole clear out the backlog of GitHub requests.
O’Toole recently asked them to formally join the organization as part of the newly created Pango Network Lineage Designation Committee, which discusses and makes decisions about variant names. Another committee, which includes lab leader Rambaut, makes higher-level decisions.
“We’ve got a website, and an email that’s not just my email,” O’Toole says. “It’s become a lot more formalized, and I think that will really help it scale.”
A few cracks around the edges have started to show as the data has grown. As of today, there are nearly 2.5 million covid sequences in GISAID, which the Pango team has split into 1,300 branches. Each branch corresponds to a variant. Of those, eight are ones to watch, according to the WHO.
With so much to process, the software is starting to buckle. Things are getting mislabeled. Many strains look similar, because the virus evolves the most advantageous mutations over and over again.
As a stopgap measure, the team has built new software that uses a different sorting method and can catch things that Pango may miss.
Disability rights advocates are worried about discrimination in AI hiring tools
Making hiring technology accessible means ensuring both that a candidate can use the technology and that the skills it measures don’t unfairly exclude candidates with disabilities, says Alexandra Givens, the CEO of the Center for Democracy and Technology, an organization focused on civil rights in the digital age.
AI-powered hiring tools often fail to include people with disabilities when generating their training data, she says. Such people have long been excluded from the workforce, so algorithms modeled after a company’s previous hires won’t reflect their potential.
Even if the models could account for outliers, the way a disability presents itself varies widely from person to person. Two people with autism, for example, could have very different strengths and challenges.
“As we automate these systems, and employers push to what’s fastest and most efficient, they’re losing the chance for people to actually show their qualifications and their ability to do the job,” Givens says. “And that is a huge loss.”
A hands-off approach
Government regulators are finding it difficult to monitor AI hiring tools. In December 2020, 11 senators wrote a letter to the US Equal Employment Opportunity Commission expressing concerns about the use of hiring technologies after the covid-19 pandemic. The letter inquired about the agency’s authority to investigate whether these tools discriminate, particularly against those with disabilities.
The EEOC responded with a letter in January that was leaked to MIT Technology Review. In the letter, the commission indicated that it cannot investigate AI hiring tools without a specific claim of discrimination. The letter also outlined concerns about the industry’s hesitance to share data and said that variation between different companies’ software would prevent the EEOC from instituting any broad policies.
“I was surprised and disappointed when I saw the response,” says Roland Behm, a lawyer and advocate for people with behavioral health issues. “The whole tenor of that letter seemed to make the EEOC seem like more of a passive bystander rather than an enforcement agency.”
The agency typically starts an investigation once an individual files a claim of discrimination. With AI hiring technology, though, most candidates don’t know why they were rejected for the job. “I believe a reason that we haven’t seen more enforcement action or private litigation in this area is due to the fact that candidates don’t know that they’re being graded or assessed by a computer,” says Keith Sonderling, an EEOC commissioner.
Sonderling says he believes that artificial intelligence will improve the hiring process, and he hopes the agency will issue guidance for employers on how best to implement it. He says he welcomes oversight from Congress.
We just got our best-ever look at the inside of Mars
NASA’s InSight robotic lander has just given us our first look deep inside a planet other than Earth.
More than two years after its launch, seismic data that InSight collected has given researchers hints into how Mars was formed, how it has evolved over 4.6 billion years, and how it differs from Earth. A set of three new studies, published in Science this week, suggests that Mars has a thicker crust than expected, as well as a molten liquid core that is bigger than we thought.
In the early days of the solar system, Mars and Earth were pretty much alike, each with a blanket of ocean covering the surface. But over the following 4 billion years, Earth became temperate and perfect for life, while Mars lost its atmosphere and water and became the barren wasteland we know today. Finding out more about what Mars is like inside might help us work out why the two planets had such very different fates.
“By going from [a] cartoon understanding of what the inside of Mars looks like to putting real numbers on it,” said Mark Panning, project scientist for the InSight mission, during a NASA press conference, “we are able to really expand the family tree of understanding how these rocky planets form and how they’re similar and how they’re different.”
Since InSight landed on Mars in 2018, its seismometer, which sits on the surface of the planet, has picked up more than a thousand distinct quakes. Most are so small they would be unnoticeable to someone standing on Mars’s surface. But a few were big enough to help the team get the first true glimpse of what’s happening underneath.
Marsquakes create seismic waves that the seismometer detects. Researchers created a 3D map of Mars using data from two different kinds of seismic waves: shear and pressure waves. Shear waves, which can only pass through solids, are reflected off the planet’s surface.
Pressure waves are faster and can pass through solids, liquids, and gases. Measuring the differences between the times that these waves arrived allowed the researchers to locate quakes and gave clues to the interior’s composition.
One team, led by Simon Stähler, a seismologist at ETH Zurich, used data generated by 11 bigger quakes to study the planet’s core. From the way the seismic waves reflected off the core, they concluded it’s made from liquid nickel-iron, and that it’s far larger than had been previously estimated (between 2,230 and 2320 miles wide) and probably less dense.