For scientists, 5 January was a turning point in the fight against the coronavirus. That day, a team led by Prof Yong-Zhen Zhang at Fudan University in Shanghai sequenced the genetic code of the virus behind Wuhan’s month-long pneumonia outbreak. The process took about 40 hours. Having analysed the code, Zhang reported back to the Ministry of Health. The pathogen was a novel coronavirus similar to Sars, the deadly virus that sparked an epidemic in 2003. People should take precautions, he warned.
The Chinese government had imposed an embargo on information about the outbreak and Zhang and his co-workers were under pressure not to publish the code. The blackout couldn’t hold. On 8 January, news broke about the nature of the pathogen and was confirmed a day later by Chinese authorities. To sit on the code now seemed ridiculous.
Eddie Holmes, an evolutionary biologist at the University of Sydney, and a collaborator of Zhang’s, called him to push for publication. Zhang was buckling up on a flight bound for Beijing. As the plane left the runway, they two agreed to break the gagging order. On 11 January Australia time, the day China announced its first official death from the infection, Holmes published the sequence on a website called virological.org. It was a crucial act for researchers around the world. Holmes calls it “ground zero for the scientific fight back against the disease”.
It was the beginning of a remarkable, unprecedented global effort to test, treat and ultimately vaccinate against Covid-19. As one scientist put it: “In the last 11 months, probably 10 years’ work has been done.”
Nothing makes sense in 2020 outside the shadow of the pandemic. The horrendous number of deaths and families bereaved; the destruction of businesses and livelihoods; the harms to mental health, still to be tallied; the failures of governance and leadership; the countless lost opportunities. And nor does the call to arms, the frantic mobilisation of global science. In labs and hospitals around the world, and from computers on their kitchen tables, researchers came together to tackle the crisis. “Everybody who has some expertise to offer has literally dropped everything, and has been working on nothing but Covid,” said Gabriel Leung, the dean of medicine at Hong Kong University and an adviser to the Hong Kong government. Francis Collins, the director of the US National Institutes of Health (NIH), the largest funder of biomedical research in the world, is in awe of the response. “I have never seen anything like this,” he said. “It has been all hands on deck.” The phenomenal effort will change science – and scientists – for ever.
To publish the virus’s genetic code was to fire a starting pistol. As governments nervously watched to see if China could contain the virus, researchers got cracking. It took two days for the NIH, which partnered with the biotech company Moderna, to design a vaccine from the code. At Oxford University, a team led by Sarah Gilbert, professor of vaccinology, did much the same. Others, such as the German firm BioNTech, were also quick off the blocks.
Cepi, the Coalition for Epidemic Preparedness Innovations, had already swung into action. Set up in 2017 in the wake of the Ebola crisis, Cepi offered a radical new approach to ensure the world did not respond to disease outbreaks as sluggishly in the future. Before alarm bells rang in Wuhan, the organisation had kickstarted work on vaccines for a handful of priority pathogens, including Mers-CoV, the coronavirus behind Middle East respiratory syndrome, which emerged in 2012 in Saudi Arabia. Further investments backed “rapid response platforms” – new approaches to make vaccines fast – should an unknown pathogen, dubbed Disease X by the World health Organization, rear its head. It gave vaccine research momentum before the virus even appeared.
“We always had in the back of our minds that if something hit, we would have to pivot to whatever was the new emerging disease,” said Melanie Saville, Cepi’s director of vaccine research and development. Before knowing whether coronavirus would take off, Cepi exercised a “live fire” option in their contracts. They targeted four groups at first: Moderna and the German firm CureVac were both developing RNA vaccines, the US biotech firm Inovio was making DNA vaccines and the University of Queensland had “molecular clamp” technology to rapidly develop vaccines. “These were people we were already working with. They could hit the ground running,” said Saville.
It wasn’t the only race afoot. Armed with the virus’s genetic sequence, teams around the world identified strands of the code that distinguished the pathogen from other viruses, including six other coronaviruses that infect humans. Among them were Mers-CoV and Sars-CoV, the pandemic strain from 2003-04 named after the severe acute respiratory syndrome it causes. In less than two weeks, scientists had sensitive tests for the disease, a critical step in the fight back.
‘The diabolical aspect’
The simplistic question at the start of an outbreak is how bad is this thing going to get? The answer comes in many measures that are now part of everyday discourse. How does it spread? What are the symptoms? What is the incubation time? When are patients most infectious? To what extent are those who have recovered safe from reinfection? How long does immunity last? What is the R – the number of people an infected person, on average, will pass the virus on to? How does the disease harm people? What proportion of the infected die, and who are most likely to succumb? In January, all these questions needed urgent answers.
As patients poured into hospitals in China, doctors scrambled to gather information. Hasty write-ups and rushed analyses poured on to preprint servers, the online repositories that host draft manuscripts prior to review and publication in journals. Imperfect though the data was, this sharing was unprecedented and invaluable: a picture steadily emerged. The virus spread like many other respiratory infections, with droplets from the airways a main route. Once the infection had taken hold, a fever and cough might emerge and many lost their sense of smell or taste. The R number depends on how people behave, but in January, Leung and others reported R to be from 1.4 to 3.9. During the 1918 flu pandemic R was about 1.8. In the 2009 swine flu pandemic it stood at 1.46.
Doctors noticed early on that infections spread in bursts and clusters. As international teams analysed these clusters, a grim realisation dawned. Patients with Sars-CoV and Mers-CoV fell ill before becoming highly infectious, making the outbreaks containable. But that often wasn’t the case with the new coronavirus, Sars-CoV-2. Many spread the infection before symptoms appeared, and some never fell ill at all. Collins calls it “the diabolical aspect” of the virus. “It really threw us for a loop in terms of the usual methods of public health containment just not working very well, because people don’t even know they’re potentially a super-spreader,” he said.
Field data allowed scientists to track the outbreak as it spread through cities, countries and continents. That information fuelled more science. In the hands of outbreak modellers, the data informed projections about how the pandemic would evolve.
In the UK, ministers are advised on such matters by the scientific pandemic influenza group on modelling, or Spi-M, so named because pandemic influenza has long been considered the most pressing infectious disease threat. In response to the outbreak, Graham Medley, professor of infectious disease modelling at the London School of Hygiene and Tropical Medicine, who chairs Spi-M, quickly expanded the group to bring in more brains. The move brought the best outbreak modelling groups across the country together for the first time. “It’s his personality that has brought this together,” said Julia Gog, a member of Spi-M and professor of mathematical biology at the University of Cambridge. “He is ultra-collaborative. It’s never about him, but what we as a group can do.”
An issue rarely commented on in the mass mobilisation of science during Covid is the distraction of well-meaning but less informed researchers. Enthusiastic but inexpert scientists muddied waters and wasted time throughout the crisis. Modelling was not spared the problem. While Spi-M brought focus and expertise to questions of how the outbreak would progress, it seemed at times like anyone with a maths PhD, or even without, knew better. Modelling from the Spi-M teams, including the Imperial College London group led by Neil Ferguson, a professor of mathematical biology, underpinned the UK’s first national lockdown in March. The models, channelled through the Scientific Advisory Group for Emergencies (Sage), showed that without a dramatic reduction in contact between people, hospital admissions and deaths could soar. The lockdown left Gog and her brother at their mum’s home in Sussex. The family made an agreement to have dinner around the table whatever time Gog finished work, even if it was 11.30pm.
Before the lockdown, the Wellcome Trust helped build a consortium of geneticists to sequence coronavirus genomes from a proportion of those infected. This established a level of genetic surveillance never seen before in a disease outbreak. It meant virus genomes could be compared, allowing scientists to monitor mutations, investigate local outbreaks and track the spread of the virus. The Covid-19 UK genomics (Cog-UK) consortium draws on more than 200 academics and NHS scientists who read and deposit virus genomes in the Cloud Infrastructure for Microbial Bioinformatics (Climb) database, funded by the Medical Research Council.
Globally, scientists have sequenced more than 200,000 Sars-CoV-2 viruses and nearly half come from Cog-UK. The data is shared immediately. Armed with viral code from a flare-up, public health teams can investigate. Did a care home cluster come from a single infected person? Have disparate outbreaks been seeded by holidaymakers returning from the same spot? “You can’t reconstruct exactly who infected whom, but it gives you a picture of how transmission is occurring,” said Andrew Rambaut, professor of molecular evolution at the University of Edinburgh. “It’s very much about situational awareness. We know a lot about what is going on in the UK epidemic by comparing these virus genomes on a day-to-day basis.” In June, genetic surveillance revealed that the UK’s epidemic had grown faster than expected because of an influx of cases from Spain and France.
Genetic surveillance acts like an early warning system by picking up worrisome mutations. The coronavirus acquires random mutations all the time and while most have no real effect, some could change its behaviour. Nailing down a mutation’s impact is far from easy. A mutated form might spread fast because a carrier happened to mix with lots of people, rather than the virus transmitting more easily. One mutation that has caught scientists’ attention is called D614G. The mutated virus quickly became the most common form in the UK and lab tests suggest it may spread slightly faster than the unmutated one.
Where and how some scientists work has also changed. Before Covid struck, Akiko Iwasaki, professor of immunobiology at Yale University, wasted hours in airport security lines, waiting lounges and taxis, travelling domestically and internationally week after week. She now coordinates her lab team’s work from home and gets far more done. “It’s extremely efficient,” she said. “I can devote every minute to science.”
“The Covid research is going at lightspeed,” she added. “People are working around the clock, trying to figure things out in a collaborative manner. I’ve reached out to so many people around the globe to collaborate on various aspects of Covid research and they have been uniformly positive interactions.”
Lab work around the world quickly confirmed that Sars-Cov-2 infects human cells by latching on to proteins called ACE2 receptors that protrude from cell surfaces. The infection tends to start in the upper airways. There, the virus can contaminate mucus in the respiratory tract and be released in tiny droplets through coughs, talking and breathing. In serious cases, the infection spreads to the lungs where it can cause pneumonia and potentially lethal inflammation.
Iwasaki has focused on some of the crucial questions at hand. Chief among these is how the immune response differs in patients with mild, moderate or severe disease. Beyond antibodies that disable the virus, the immune system unleashes T cells that clear the virus by destroying infected cells. It turns out that the disease hits hard when the immune system mounts a discoordinated attack on the virus. Sex differences matter, too. Women typically launch a better T cell immune response than men, and men with very low T cell responses tend to fare worse. “It’s one of those discoveries we’re very excited about,” she said. “It’s starting to reveal some intrinsic differences between male and female immune response and that may explain some of the differences we see in the disease.” Other patients in the lab studies cannot seem to clear the virus, or have long Covid – medical problems that persist for months.
Beyond running her lab, Iwasaki has made extraordinary efforts to explain the science of Covid-19 to the public, in part to counter the wealth of misinformation surrounding the disease. She has had to deal with sexist remarks online, as have other prominent female scientists. “It’s really distracting, because not only am I dealing with science and communication, I have to deal with justifying my expertise. It takes not only time but emotional energy,” she said.
‘A result that changed the trajectory’
The meticulous work at Iwasaki’s lab, and others like it around the world, has helped build a picture of how the virus behaves. The knowledge gained will pave the way for better treatments and prevention strategies. Those are largely for the future though. As hospitals began to swell with Covid-19 patients, doctors knew they needed to find existing drugs that might help. With the death rate reaching a third among UK admissions in the spring, effective treatments could not come fast enough.
Help came in a form that will reshape how clinical trials are performed in future outbreaks. Two days into January, Peter Horby, a professor of emerging infectious diseases at Oxford University, started work with Chinese colleagues who had been sent to Wuhan from Beijing. Together they set up a trial in the city to see whether the antiviral drugs remdesivir and lopinavir/ritonavir, an anti-HIV combination, helped reduce disease. As the trial got under way, Horby applied for a grant to continue the work in China. By the time the funding came through infections were falling in Wuhan but rising in Europe. The funder gave Horby the green light – but said the trial must run in the UK.
Horby teamed up with Martin Landray, another professor of emerging infectious diseases at Oxford, who brought with him the full machinery of the university’s clinical trials unit. The pairing married two traditions: tropical medicine and the kind of large-scale trials normally used to assess treatments for cardiovascular disease, high blood pressure and the like. In early March, Horby and Landray went to see Chris Whitty, England’s chief medical officer. He gave the go-ahead for what became Recovery, the world’s largest trial of drugs for Covid-19.
“We knew we needed to get started quickly, so we wanted drugs that were ready now,” Horby said. That meant trialling whatever looked promising in the medicine cabinet. A subgroup of Nervtag, the UK government’s New and Emerging Respiratory Virus Threats Advisory Group, compiled a shortlist of drugs that went first into the trial. They included the malaria drug hydroxychloroquine, the HIV drug lopinavir/ritonavir and the steroid dexamethasone. The trial was later expanded to include more medicines, old and new.
It hasn’t all been plain sailing. Horby expected unscientific claims to surface in the pandemic, as they had during the Ebola crisis. But the nature of the misinformation surprised him. Donald Trump made baseless claims for hydroxychloroquine supported by his trade adviser, Peter Navarro. The commissioner of the US Food and Drug Administration (FDA) falsely declared that blood plasma infusions from recovered patients would save 35 lives in every 100 who received it. “You expect fringe elements, but this was from the establishment,” said Horby.
In early June, the Recovery trial found no clinical benefit from hydroxychloroquine in patients in hospital. The announcement sparked a barrage of attacks from advocates of the drug. “There were two faces to it. A rigorous and strong scientific response fighting an ill-informed, non-scientific agenda,” Horby said.
Less than two weeks after the hydroxychloroquine result the Recovery trial hit gold. The cheap and widely available steroid dexamethasone was shown to cut deaths by up to a third in hospital patients sick enough to need supplemental oxygen. It was the first real good news of the pandemic: a treatment everyone could use to save lives. Horby told his boss about the finding over a Skype call one evening. His boss got up and jumped around the room, revealing red shorts below his sober work shirt.
“It’s the first time we’ve got a result in the middle of an outbreak that’s changed the trajectory,” Horby said. “We’ve finally shown you can do large-scale clinical trials in a health emergency and you can have a result in the emergency that changes things, not just post hoc for the next one, but during the ongoing outbreak.”
Over in Bethesda, Maryland, home to the NIH, Francis Collins had brought the full power of the agency to bear on the crisis. It was clear in March that much of the US response to Covid was “scattershot”, he said. Academics and companies with the best intentions had launched projects on vaccines, therapeutics and diagnostic tests, but there was no coordination, no plan. “The risk was that an awful lot of the energy would go into unfruitful investigations,” he said.
Collins took an exceptional step. He formed a partnership across the FDA, the Centers for Disease Control and Prevention, and the largest pharmaceutical companies to set priorities and make them happen. Known as Activ, for Accelerating Covid-19 Therapeutic Interventions and Vaccines, the collaboration took two weeks to establish. In normal times it would have taken years. “Everyone just felt they had a responsibility to bring all the resources and skills and vision together and figure out how to do this,” Collins said. When Activ started it had a longlist of 640 different therapies that might help treat Covid-19. This was whittled down to a manageable number and the drugs fed into trials.
The NIH moved on to testing. With $1.5bn appropriated by Congress, the agency issued a call for rapid diagnostic tests. Bypassing the usual drawn-out process, applicants submitted their best ideas for review. From about 700 applications, more than 100 were deemed good enough to throw into the “shark tank”, a Dragons’ Den-style committee of experts on business, engineering, manufacturing and supply chains. Most ideas fell short, but 22 received funds. “We’re performing the role that would normally be carried out by a venture capital firm, but it’s working fantastically well,” said Collins. Within the month, they are expected to contribute an extra 2m Covid tests a day.
‘We’ve done things people would have said were not possible’
It has, then, been a remarkable year. Globally, researchers isolated the virus and made rapid tests; monitored its evolution and how it spread; teased apart the virus’s workings and uncovered how it harms. They handed doctors drugs to help patients survive and produced at least three vaccines, from Pfizer/BioNTech, NIH/Moderna and AstraZeneca/Oxford that prevent people getting sick.
We should not get carried away though. Hong Kong University’s Gabriel Leung believes much of the scientific effort has been “first rate”, both from a biomedical standpoint and in debunking the torrent of myths, untruths and conspiracies. But it has fallen short in important ways. Researchers had too little understanding of the mental health consequences of Covid, he said, and either failed to recognise or failed to counter the deep health inequities the pandemic has exposed. Worse, he sees the introduction of vaccines repeating the same failure. “Unless the whole world comes together to allocate and distribute vaccine, we are about to deal vulnerable and disadvantaged groups a double whammy,” he said.
Another glaring issue is how well – or not – governments acted on the science in a timely and efficient way, Leung added. Poor translation of science into policy worsened the pandemic. And countries, such as the UK, that seemed well-prepared on paper turned out not to be. Countries rank their capacity to handle health emergencies according to the WHO’s Iinternational health regulations. The UK ticks nearly every box for preparedness. “Revisiting those guidelines and checkboxes is one obvious thing to do,” Leung notes.
The relentless intensity of research in the pandemic has taken its toll on scientists. Gog said she and many colleagues had made the decision to work on the outbreak knowing it would have a long-lasting effect on their health. Would she make the same decision again if she knew what was coming? “With the full wisdom of hindsight I would have said yes. If I knew what it was going to be like, I would have said no, I can’t do it, I’ll break. You change. I’m not the same person I was in February. If I look through what’s happened in the past week, I can see 10 things that would previously have sent me into a meltdown, but not any more.”
Francis Collins agrees it has been a long haul. “It has been utterly exhausting at times. I’ve been involved in plenty of intense scientific competitions but this is different. You have this sense that every day counts, that what you are working on may save some lives and that you cannot make mistakes, you cannot afford to give anything less than 100%.”
Leung put it more succinctly. “Knackered? Definitely. Battered? Not yet.”
Science, like scientists, has been changed by Covid. New collaborations, funding routes and systems for sharing data will shape research from now on. The technologies developed for rapid tests will be adapted for other infectious diseases. In future pandemics, genetic surveillance will be the norm with scientists sequencing pathogens for every positive test as a matter of routine. Clinical trials, which have become more complex, smaller and more expensive, should run continuously in the background of hospital care. “That makes it simple and scalable. You can get questions answered much faster and much more cheaply,” Horby said.
The vaccine work may leave the most exciting legacy. By doing as much work in parallel as possible, and teeing-up volunteers early, removing gaps between trials and manufacturing doses before trials conclude, vaccine teams had shots ready for arms on a timeframe many considered impossible. A new standard has been set.
Meanwhile, new vaccine technology has shown its worth. When Covid-19 emerged, no vaccine based on RNA had ever been approved. The new vaccines inject genetic material – mRNA (messenger ribonucleic acid) – into the body that contains the instructions to make the so-called “spike” protein of the coronavirus. In response to these proteins, the body’s immune pathways are activated – a response that offers protection should we encounter the virus itself.
The impressive results from Pfizer/BioNTech and NIH/Moderna have thrust the technology to the forefront. “I think there’ll be an explosion in investment in RNA around the world,” said Robin Shattock, professor of mucosal infection and immunity who is developing an RNA vaccine for Covid at Imperial College London.
The RNA work has its roots in experimental, personalised cancer therapies. Scientists realised that if they could identify unique proteins on the surface of a patient’s tumour, they could send in an RNA vaccine that triggers the immune system to attack the malignant cells. The pandemic has shown the potential for fast, safe and effective RNA vaccines, boosting confidence in RNA cancer therapies, vaccines for other infectious diseases and the next inevitable global outbreak.
There are still hurdles to overcome. RNA vaccines do not come cheap. Shots of the BioNTech and Moderna vaccines cost roughly 10 times more than the Oxford vaccine. Part of the problem is the price of reagents, but Shattock sees the industry scaling up and the cost duly falling. Another issue is storage. Pfizer’s vaccine must be stored below -70C, making distribution a nightmare in many countries. Shattock has found a way to store his RNA vaccine for five or six months at standard fridge temperatures, but more work lies ahead.
Shattock points out that the UK has no biotech firms that are heavily invested in RNA. Without them, he fears the country may lag behind in the coming RNA revolution. BioNTech received €375m (£337m) from the German government and a €100m loan from the European Investment bank to develop its vaccine. Moderna amassed $2.5bn (£1.9bn) in research and supply funding from the US government.
Whatever happens in the UK, if costs fall for RNA vaccines, their impact could be striking. Unlike conventional vaccines, RNA vaccines do not need facilities the size of a B&Q warehouse to churn out doses. Production plants the size of a few shipping containers could be set up around the world. Then, the next time a lethal virus emerges, countries could start making vaccine immediately. “The manufacturing plant is like the hardware and the RNA is the software. Instead of waiting for a single centre, you can disseminate the sequence around the world and many sites can get manufacturing at the same time,” said Shattock.
Beyond the technical advances, Collins sees a change in mentality, and a new standard to be held to. Having shown what can be done, who can now say that tests, vaccines and drugs cannot be developed and approved in months? “A lot of what has happened this year are things that people would have said were not possible,” Collins said. “We have now disproved that scepticism. It will be very hard for scepticism to carry the day in the future.”
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