Learning to beat a virus
On January 11, 2020, Chinese authorities announced the first death from a new coronavirus. At the time, the virus had only infected 59 people, and it was suspected of having spread from a seafood market in the city of Wuhan. On the same day, Chinese researchers made the genetic sequence of the virus public, then named the new coronavirus nCov-2019. With approximately 30,000 characters, this code would allow scientists to design one of the main candidate vaccines against the infection in three days.
So somehow, January 11, the day the world learned of the death of Mr. Zhang from Wuhan (the man is identified only by his last name), also marked the arrival of a small but significant breakthrough that would eventually lead to the start. the end of the pandemic. Within two months, a 76-year-old man from Karnataka with multiple comorbidities became the first Indian to die from the virus, and five days later, on March 15, India declared the outbreak a disaster.
Since then, scientists, physicians, public health officials, and pharmaceutical companies around the world have embarked on a race against time, reorienting their collective focus and energies in a way that has paralleled some of the greatest collaborative efforts in history, like the Manhattan Project or the Apollo program.
This race has largely focused on trying to understand the virus and the disease it causes, and finding ways to save lives and stop the virus. In the past year, PubMed Central, the largest database of free and open access research literature in the biomedical sciences, has made 89,000 presentations on Covid-19.
As the year ends, major new mutations of the virus have been detected in the UK, South Africa and other countries, leaving us with more questions to answer; For starters, what does this mean for immunity and vaccines?
THE FIRST SIGNS
It would not be until January 20 that the world would learn that the virus was spread between humans, and on January 26, that it could also spread between and by asymptomatic individuals. At the time, the number of confirmed infections in China had reached 2,000, and these two crucial events were the first indicators of the potential of the coronavirus to cause a pandemic.
When the world entered the spring of 2020, the virus took over more Asian regions (Japan, Singapore, Hong Kong) and its first cases emerged in Europe and the United States. At this point, the researchers were able to determine that Sars-CoV-2, as it was officially called as of February 11, had a basic breeding number (R0, or R null) of 2.4 to 2.6. This meant that, on average, two infected people would transmit the virus to five more, and those five to at least 31 more people.
These figures project an exponential explosion in cases. On March 16, five days after the World Health Organization (WHO) declared Covid-19 a pandemic, researchers at Imperial College London predicted that if nothing was done to control the epidemic, at least 510,000 people would would die in the UK and 2.2 million in the UK. the United States. The need was clear: lock in to flatten the infection curve so hospitals could avoid a surge of cases.
For the remainder of the year, the need to flatten the curve would lead countries around the world to spin into a reluctant game of cat and mouse to contain the spread of the virus. Among the populous nations, India was one of the few that stalled early in the outbreak, an approach criticized for having caused widespread economic damage, but which may also have given the nation time to improve its testing and treatment capabilities.
The need to blockade cities has been one of the approaches on which the government, public health authorities and experts have largely agreed to during the course of the pandemic. The initial stage of the pandemic was marked by conflicting evidence and recommendations, especially about whether people should wear masks.
After initially saying that masks did not help the uninfected, the WHO on June 6, almost three months after declaring the pandemic, updated its guide to advise people to wear masks in regions with community transmission. At that time, the total global infections was 6.6 million and deaths close to 400,000.
At this point, it also became clear that sharing the same air posed the greatest risk, but close contact tracing would later show that not everyone in an enclosed space would contract the virus – the way air flowed in those spaces played a role. role, but also made the duration of contact. Some activities, such as singing or talking loudly, shoe leather epidemiologists found, increased the likelihood of infections.
The understanding of how to treat Covid-19 patients also evolved. As the virus swept through the elderly populations of Italy, Spain and France in April, doctors began using drugs with a new purpose, including those that showed promise in the treatment of HIV / AIDS, broad-spectrum antivirals like remdesivir and plasma-rich antibodies from recovered patients. Over the course of the year, there have been hardly any major advances in treatment. Remdesivir and favipiravir have shown mixed results, the anti-HIV drugs lopinavir and ritonavir were shown to be ineffective; even the benefits of convalescent plasma therapy have not been clear. One drug appeared to have clear life-saving benefits: dexamethasone.
The fact that dexamethasone worked was linked to a worrying new facet of Sars-CoV-2: It didn’t just cause respiratory disease. People who developed severe symptoms or succumbed to the virus showed signs of widespread organ damage. Blood tests and autopsies revealed that the disease would often put the body on a path of war with itself, confusing people’s immune systems to speed up.
This caused damage to organs such as the lungs, kidneys and heart, scans and autopsies revealed. Some people also developed blood clots that could trigger strokes, while a worryingly large number suffered persistent “prolonged Covid” symptoms, often unable to regain energy, focus, or sense of smell for months after an infection.
In December, virologists and geneticists in the UK discovered a new strain of the virus, with more genetic modifications than seen in the 12 months since it began to spread. The strain appeared to be more infectious, becoming more prevalent than other strains. Countries around the world have already started to respond to this: London declared a total lockdown just days before the Christmas holidays and several countries in Latin America and Europe have imposed flight bans on the UK. India too.
More research will be needed to determine whether the new strain poses a threat to current efforts to contain the disease, which have themselves struggled to slow the march of the pandemic. It is also unknown whether the mutation, or whatever might occur, could render current candidate vaccines ineffective. Vaccines are usually broad spectrum – they target multiple viral proteins to avoid an eventuality like this – but there is always the chance that a virus could mutate enough to avoid them.
The sheer volume of research now available in open source repositories like PubMed Central represents a relentless mission by scientists around the world to not only uncover the secrets of the virus, but also the millions of factors at play in its spread.
This mission has brought together not only biomedical researchers, but also mathematicians, computer modelers, and artificial intelligence experts. His frantic efforts capitalized on decades of advancements in medical science. Scientists can now inspect its structural secrets. They have even been able to visualize how its protruding spike proteins, the component it uses to adhere to and infect cells, combine in groups of three and can rotate as if mounted on a hinge, enhancing their ability to infect targets. Top-of-the-line biotechnology, such as gene editing, has been repurposed to add to the arsenal of tools the world has deployed against Covid-19. Pharmaceutical companies have created laboratory-grown antibodies, which are similar to building their own army of specialized coronavirus hunters.
Even the cutting edge of computing promises to bolster the human race’s ability to combat such threats. Take, for example, the November breakthrough from artificial intelligence firm DeepMind, which was able to accurately determine the shape of proteins. Such technology can help take a closer look at Sars-Cov-2, helping tailor therapies and medications.
But the most watched among these advances is the rapid development of a vaccine: the candidate mentioned at the beginning of this trial, for example, was approved just over 11 months later, while normally the process (vaccine development, testing and approvals ) can normally take about a decade.
This vaccine was developed by Moderna, in collaboration with the US National Institute of Allergy and Infectious Diseases, and used a platform that itself has been hailed as innovative. Another American company, with a German partner, uses the same platform and both have proven highly effective. Several other vaccine manufacturers are racing against time to complete the testing process. These include old platforms, such as the many candidates that use a weakened or inactivated virus to elicit an immune response, and new ones, such as the Oxford-AstraZeneca Trojan horse-like strategy known as a viral vector.
Undoubtedly, many unknowns remain: can vaccines leave a lasting immunity? Will the virus mutate to defeat it (and our immune system)? Are there more long-term effects that we haven’t identified yet?
It is not known when modern science will unravel these mysteries. But if 2020 is any indication, scientists and doctors are likely to find a way for the world to live with the virus, if not eradicate it completely.
It is also true that the world, scientifically and technologically, has never been better prepared to deal with a virus of its nature than at this time. The scientific legacy of fighting this virus is likely to fuel this preparation and help achieve what experts have always sought: more attention and funding for health and science.