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What we know about the virus so far
Let’s start with the basic questions.
Immunity against Covid-19 seems to last longer than we initially thought In: New York Times (16 August)Are you immune to SARS-CoV-2 after you’ve caught the virus? And if so, for how long? These are two of the most important questions regarding the pandemic. If we can only build up weak or temporary immunity, finding a vaccine will be a huge challenge and herd immunity will be next to impossible.
Luckily, science probably has some good news about this. Several studies have shown that our immune system continues to react to coronavirus even months after infection. This also applies to people who didn’t get very sick from the virus. Thus, if these results will be replicated through further research, we can cautiously start hoping for a corona-free future. This promising medicine could cure coronavirus patients more quickly In: New England Journal of Medicine (22 July)
So far, there aren’t a lot of medicine on the market that have proven effective against Covid-19. Until now, there was only Remdesevir, an anti-inflammatory which was found to cure coronavirus patients more quickly. In this podcast, a second useful medicine is being discussed: Dexamethasone. A recent study found that this anti-inflammatory reduced the mortality rate among severely ill patients by 20 to 30 percent. How the world’s first coronavirus vaccine was developed In: Wired (13 May)
On 16 March, Jennifer Haller became the first human to be injected with a coronavirus vaccine. Historically speaking, the chance of a successful vaccine is a meagre 6 percent during trials. The art is to deliver genetic material into someone’s body, which instructs the cells to replicate (harmless) parts of the virus. Then, the immune system will combat the virus by making antibodies.
Pharmaceutical company Moderna, which hopes to produce a million doses of a vaccine (mRNA-1273) at the end of the year, worked with the US government’s Vaccine Research Center. Scientists at the latter institute discovered how to mimic the characteristic spikes of the virus, while Moderna researched the genetic “delivery” of the “dummy virus”.
Meanwhile, over a hundred vaccines are in development worldwide, but the US government believes in the vaccine made by Moderna. It has approved a $500m investment in the company. Moderna expects the results regarding the world’s first coronavirus vaccine to come in at the end of June. A visual simulation of spreading coronavirus by sneezing In: New York Times (14 April)
There is still so much we need to understand about Covid-19 and its transmission. But studying similar respiratory diseases like influenza can help us understand why social distancing is so important, and why it is necessary to wear face masks.
This 3D simulation by the New York Times is a great visual reminder that an infected person’s cough, sneeze or breath can travel quite far – way beyond 1.5 metres – and can last in the air for up to 20 minutes in closed quarters. At the bottom of the piece there is even an augmented reality experience that you can try yourself while grocery shopping (by using a cellphone). Scientists around the world have never worked together as closely as they do now In: New York Times (1 April)
When a scientist makes a brand-new discovery, they usually start by writing a research paper. In the age of corona, new knowledge is being shared with the rest of the academic world as quickly as possible. An example: a virologist from the University of Pittsburgh examined a ferret that had contracted Covid-19 and developed a fever. Two hours later, the whole world knew about it, after a conference call with the World Health Organization.
While political leaders like Donald Trump and Xi Jinping are posturing patriotically, scientists have largely abandoned nationalism and personal ambition. Scientists are working together more effectively. US labs are working with their peers in France, Austria, Norway and India. Chinese researchers shared their genetic analysis of the virus with the world. And scientific journals are publishing information faster than ever, often completely free and available to the public. Why the coronavirus is so effective In: The Atlantic (20 March)
The coronavirus has spikes on the outside, which allows it to attach very easily to a protein called ACE2, which is located on the surface of our cells. Those spikes consist of two halves. If the spike splits in two, the virus can penetrate a cell.
Coronavirus is being helped by our own bodies. Splitting the “bridge” connecting the two halves requires an enzyme called furin – which is found in large quantities in our own tissues. The current configuration of the virus works perfectly to infect people, or worse. That’s why the virus hasn’t mutated much yet: a virus only mutates when it is no longer effective. Understand the coronavirus in eight minutes In: Kurzgesagt (19 March)
In just eight minutes, YouTube channel Kurzgesagt explains what coronavirus is. In the lungs, the virus attaches itself to cell membranes and instructs the cell to keep cloning the virus.
The coronavirus can also affect the immune system, so it starts attacking your own healthy cells as well. Once your immune system is exhausted, bacteria can move in and cause even more damage to the body.
Their advice to prevent infection? Wash your hands as if you’ve just cut up jalapeños and want to put in your contact lenses. Sneezing into your elbow really works to avoid spreading coronavirus In: MythBusters (Classic: 10 November, 2010)
MythBusters, a popular TV science show on Discovery Channel, tested three methods to catch emissions of droplets from sneezing – which is how the coronavirus spreads to others. They tried sneezing into your hand, into your elbow and into a handkerchief.
When you sneeze into your hand, droplets from your nose and mouth can fly almost three metres through the air. Not a good idea in a society that is social distancing at a radius of 1.5 metres. The handkerchief is a better idea, but even then, droplets will pass through the cloth and land on your hands, causing you to spread the virus through hand contact.
So that’s how the virus works. But how did it spread? How could it turn into a pandemic? Why can’t we compare Covid-19 to the flu? And can it be compared to other viruses?
I read these great articles that answer those questions.
How the virus became a pandemic In: New York Times (22 March)On 31 December 2019, when at least 1,000 people were already infected, the Chinese government informed the World Health Organization about what we now know as the coronavirus. A large-scale analysis of travel behaviour based on mobile phones and social media shows that at least seven million Chinese people left the city of Wuhan, where the current pandemic began, within the month following that warning.
When Wuhan was cut off from the outside world at the end of January, the virus had already spread to 30 cities in 26 different countries. Researchers estimate that 85% of infected travellers from China travelled abroad without visible symptoms. You’re likely to get the coronavirus In: The Atlantic (24 February)
Because it is so difficult to identify, the coronavirus can spread quickly and easily. That’s the dangerous paradox of this virus. Its symptoms – fever, coughing, shortness of breath – are very similar to those caused by less harmful viruses. Patients often do not show any signs of illness at all.
Marc Lipsitch, an epidemiologist at Harvard University, expects that 40% to 70% of the world population will be infected with the virus. An effective vaccine will take at least a year or 18 months to develop, predicts pandemic expert Richard Hatchett from the Coalition for Epidemic Preparedness Innovations.
What we know from other pandemics
From the Spanish flu in 1918 to the swine flu in 2009 – pandemics have plagued mankind for many years ... And we can learn from the past.
The worst health crisis has yet to come In: New York Times (3 August)Before coronavirus, we were beating a multitude of severe diseases. In 2018, the world counted fewer malaria, tuberculosis and HIV/AIDS deaths than ever before. But the current health crisis means a major setback in the battle against these diseases. The estimated amount of extra deaths is up in the millions, mainly in low-income countries. And this is not just because the pharmaceutical industry’s attention is elsewhere now.
Most of all, it’s due to lockdowns making it impossible for people to get diagnosed and receive medicine, as they have to travel to a clinic for that. It’s also because of the cancellation of mosquito net distribution programs. And because vaccination campaigns were halted.
Worldwide, 80 percent of disease control programs against HIV, tuberculosis and malaria have been disturbed by the corona crisis. That’s a huge problem with diseases like these: resistent viruses might come into existence, so current medicine might end up ineffective when health programs are up and running again. The impact of this second, invisible health crisis will be felt for years to come. Viruses have always been with us, and they always will be In: The Correspondent (10 April)
A pandemic is usually the result of three things: human contact with animals, globalisation and technological progress. Medical historian Mark Honigsbaum explains how that works in his book The Pandemic Century.
During the first world war, soldiers contracted the Spanish flu in the trenches of northern France, which were full of animals. 1929 saw outbreaks of parrot fever in various countries due to the international trade in exotic birds. In 1976, preheated water in which bacteria could thrive led to a legionella outbreak in the US city of Philadelphia. And the Sars epidemic, which originated from a bat, was able to spread in 2003 thanks to air traffic to destinations as distant as Canada and Hong Kong.
Honigsbaum has several important lessons to share. It usually takes years to fully map out the cause and spread of a virus. And some viruses will keep popping up periodically – such as Ebola, which was first discovered in the 1970s and reappeared suddenly in 2013. What we can learn from previous pandemics In: BBC (10 March)
A pandemic may seem like a unique phenomenon, but the last global outbreak of disease was less than a decade ago. Swine flu (a global outbreak of H1N1 influenza) claimed at least 18,000 lives in 2009 and 2010. BBC’s Witness History page has compiled a wonderful collection of videos and podcasts on the biggest epidemics and pandemics of the past century: the “Spanish” flu of 1918, Sars and Ebola, but also the lesser-known Marburg virus, which emerged in Germany in the 1960s.
Doctors, virologists, lab assistants and eyewitness accounts offer details on each outbreak. The first-hand reports from people who worked on the frontline of medical crises offer an interesting historical perspective on the pandemic that their successors are now fighting. What we can learn from the Spanish flu, 100 years later In: New Yorker (Classic: 29 September, 1997)
The Spanish flu infected a quarter of the world’s population between 1918 and 1920. This article on the pandemic is a good introduction to the fields of virology and epidemiology.
An important insight is that more dangerous mutations of a virus are less likely to survive. If a virus is acutely severe, people stay inside, thus infecting fewer people. However, biologist Paul Ewald argues that the first world war made this impossible. The most severe strains were allowed to spread as sick soldiers left the trenches.
Malcolm Gladwell’s article is not a guide to the current crisis. Instead, read it as a primer on the current crisis and the enormous efforts that are being made to know more about viruses and how to protect the world from them.
What we don’t know for sure (yet)
There’s a lot we don’t know about coronavirus. As a lot of numbers, graphs and fake news are going around on social media, I think it’s important to tell you everything we don’t know yet, or simply can’t know.
This study indicates that cancer patients can continue with their treatment during the pandemic In: ESMO (4 June)Most of the medicine for cancer patients have a huge impact on their immune system. That’s why doctors feared this category of medication would increase the chance of dying from Covid-19. But a British study shows that fear was probably unjustified.
Patients who were treated with cancer medicine did not face a larger risk of dying from the coronavirus than patients who were not treated with these medicaments. The results indicate it is not necessary to interrupt cancer treatment while the pandemic is still raging on. The malaria medicine Trump endorsed for use against Covid-19 was disqualified by a spectacular study. But the data didn’t add up In: The Guardian (3 June)
Hydroxychloroquine is a malaria medicine the World Health Organization was studying as a possible remedy against coronavirus. But when a spectacular study was published in the scientific journal The Lancet at the end of May, many experiments were ended – the medicine’s side-effects were believed to be too dangerous.
A few days after the study had become world news, Australian researchers discovered the dataset that was used contained more deaths than the official statistics. Furthermore, Surgisphere, the firm behind the dataset, claimed they had data from 96,000 patients in 1,200 hospitals, but both Australian hospitals and NHS Scotland had never shared any data with Surgisphere.
Even more strange: among the six Surgisphere employees were a science-fiction writer and an adult content model. The Lancet has decided to retract the study. How many people died from coronavirus? We have the numbers, but they will never be fully accurate In: FiveThirtyEight (20 May)
We often hear the amount of deaths due to coronavirus is likely higher than the official number. That’s very plausible, because not everyone gets tested for the virus. Also, it’s not always easy to determine the exact cause of death. This FiveThirtyEight article is about the United States, but it shows how an ostensibly easily quantifiable phenomenon is, in fact, very difficult to calculate. What we do and don’t know about ‘superspreaders’ In: Science (19 May)
At the beginning of the coronavirus pandemic, everyone was talking about the “curve” of patients that had to be “flattened” by social distancing. About a month ago, people started discussing R: the number that tells us how many new infections are, on average, caused by someone who already has the virus. And now, we keep hearing about k, or the “dispersion factor”.
If k is low, it means the virus is spreading from a small group of people – also called “superspreaders”. This happened, for instance, in US choirs and meatpacking warehouses, Japanese concert venues and South Korean zumba classes. A scientist from the London School of Hygiene & Tropical Medicine estimated that 10% of infected people causes 80% of all new coronavirus cases.
This article offers an interesting explanation for superspreading: chances of it happening reportedly increase in a closed environment where people breathe and talk (loudly) in close proximity to each other. In scenarios like these, a lot of saliva particles end up in the air in a relatively small area, increasing the risk of infecting healthy bystanders. Are face masks effective? The answer is more complex than you hoped for In: Neurologica (12 May)
Do face masks actually work? There’s no easy answer to this question. It all depends on what type of mask you use and whether the person wearing it has been infected or not. And which variables should we look at to measure a mask’s effectiveness? Just the reduction in spreading virus particles through the air, or the chance those particles could infect someone else, too?
In this article, neurologist Steve Novella discusses current research regarding face masks. Turns out there’s a lot we don’t know yet, but the studies suggest it’s wise for healthcare workers to wear N95-type face masks. The rest of us wearing a regular mask probably has very limited effect, and even then only when the mask is being worn correctly. Novella’s conclusion: wear a mask in busy places, but remain as careful as if you’re not wearing one. The number that decides whether we come (and stay) out of lockdown In: The Correspondent (11 May)
To measure the course of the coronavirus pandemic, epidemiologists use the effective reproduction number – also known as R. That number indicates how many people an infected patient will infect on average. If R is 2, then the virus is spreading exponentially (1, 2, 4, 8, 16, 32, and so on). If R=1, then the outbreak is neither growing nor shrinking: every current patient infects one new patient.
Governments around the world are aiming to get the R below 1, so that the disease spreads less and less effectively. The measures target the three factors that contribute to R: the risk that someone will infect another person through contact (that risk is reduced by keeping your distance and washing your hands), the number of contacts each person has (which can be lowered eg by working from home), and the duration of the contagious period (minimised by quickly tracing infected people and putting them into isolation). Why are some countries hit harder by the virus than others? We don’t know yet In: New York Times (3 May)
Everyone is desperate to understand why some countries are doing better than others. Is it the testing? The climate? The culture? The demographics? The app? Whatever the answer is, it will help to combat Covid-19 as effectively as we can.
This article discusses what we know about potential reasons for success, but also what we don’t. It shows how notoriously difficult it is to separate correlation from causation. For every possible cause, there’s an exception that seems to disprove it. This will be food for discussion (and research) for years to come. Definitive knowledge about coronavirus? We are not even close In: The Atlantic (29 April)
Science journalist Ed Yong offers a fantastic summary of the complexity of the pandemic, and how hard it is to comprehend just how complex it is. His extensive overview is really eight separate pieces presented in a coherent framework, encompassing such topics as: what is the virus; what is the disease; how scientific research works and what’s different during the pandemic; why journalists should be less adamant about “expert opinions”; how a wealth of information and misinformation is causing confusion; why prevention is never as popular as a cure; and even more.
Each of the sections would make great reading on its own, but it’s important to view everything in context, Yong explains – especially during a pandemic: “We crave simple narratives, but the pandemic offers none.” And yet he manages to explain it all in an entertaining, understandable and simple way. These are the three most important fallacies in the coronavirus debate In: The Correspondent (6 April)
Over the past few weeks, the Netherlands feared that it was following in Italy’s footsteps in terms of corona-related deaths. Two tables with more or less equal numbers were displayed side by side as “evidence”. Lots of things went wrong there: the starting dates were chosen at random, and differed dramatically depending on if we started counting from the first death or the first hundred infections in the two countries.
Also: coronavirus data from different countries can’t be casually compared. Italy’s demographics are different than those in the Netherlands, with a much higher percentage of older people – who are more susceptible to Covid-19.
Finally, the calculation methods vary from country to country. In the Netherlands, for example, testing has been relatively limited so far, so the official number of coronavirus infections will always be lower than the actual number. Number of infected patients and total deaths might seem like reliable figures, but they actually offer a false sense of security. The trustworthiness of corona numbers depends on the frequency of testing In: FiveThirtyEight (4 April)
We keep hearing about “confirmed” cases of coronavirus. That adjective is there for a reason: the exact number of Covid-19 cases is unclear. Why is that? Not everyone is being tested since many countries have a serious shortage of tests. The result: the figures underestimate the huge scope of the problem.
The extent of that underestimation varies from country to country; some nations test often, others do so infrequently, and some are gradually scaling up the number of tests. In this article, data journalist Nate Silver shows how the reliability of coronavirus figures depends on the method of testing.
Using the fictitious country of Covidia as his case study, he shows how often the real figures get it wrong, and what that means for the oh-so-crucial R, the number that indicates how contagious an infectious disease is. The important lesson: data on cases of Covid-19 are useless as long as you don’t know how much a country is testing. How to simulate an epidemic on your own computer In: 3Blue1Brown (27 March)
You may not be an actual epidemiologist, but that doesn’t mean you can’t read up on epidemiological models. This video by 3Blue1Brown shows what’s known as the SIR model, in which the population is divided into three groups: susceptible, infected and recovered.
This simple model can be used to simulate all kinds of scenarios. What if infected cases are isolated quickly? What if you assume you overlooked a few? What effect does social distancing have? How about travel restrictions?
Models are extremely sensitive to different assumptions. As the video’s creator emphasises, the model is too simplistic to be used for formulating official policy, but it offers a good glimpse into the minds of the modellers who are playing such a vital role right now. When will there be a drug to treat Covid-19? In: The Correspondent (23 March)
The medical world’s top priority right now is developing a coronavirus vaccine. But drugs to treat Covid-19 could also alleviate the suffering caused by the pandemic. Finding a treatment won’t reduce the number of infections, but people who get infected won’t get as sick. These medicines target the proteins that accompany the virus: if a drug can block one protein in the chain of infection, the virus will become ineffective. Scientific consensus on coronavirus is not happening anytime soon In: New Statesman (23 March)
Scientific research on the coronavirus is progressing at incredible speeds, and often not subjected to peer review by other scientists. That’s just the way it is right now: there’s no time to delay before taking action.
But the science focusing on Covid-19 is not yet as far along as in fields such as climatology, two philosophers of science argue in this article. For that reason, we can’t expect every study to immediately be “true”: that’s not how science works.
It will take a while before scientists reach consensus on the coronavirus. Until then, it is important to keep a critical eye on the research being done and to expect transparency about the models that are used by the government to make policy decisions.
Guide
Coronavirus in context
The coronavirus pandemic will have far-reaching and long-lasting consequences. We want to help you understand developments around the world by providing context for the news in a carefully considered, factual and constructive way. This guide gives you the most important insights to help you understand the coronavirus pandemic.