(Bloomberg Opinion) -- Scientists all over the world are working to understand the biology of Covid-19, track its spread, predict its future and grasp the pandemic's psychological consequences. Here’s a quick look at three coronavirus science stories from the week.
Preventing the second peak: Some ideas from complexity theory
One thing the epidemiologists agree on is that once a country lifts lockdown orders, provided there’s still no viable vaccine, Covid-19 cases will build to a new peak — possibly even higher than the first. In some models, the second peak will come in the fall, depending on when lockdown orders are lifted the first time, and the still-unknown influence of warmer summer weather.
But there are strategic ways to start up the economy, says Arnout van de Rijt, a sociologist and network theorist at Utrecht University in the Netherlands. Testing and contact tracing are considered the favored solutions, but with limited resources for both, most countries will probably also need to limit the spread of new infections.
“A lot of focus now is on physical distancing… but I think network science identifies risks and opportunities that are much more nuanced and more precise than this one-sized-fits-all approach,” he says. He and his colleagues posted their model in preprint server last week. (Yes, I’m writing about unpublished papers, but only ones authored by people who regularly get published in the top journals and have a good track record.)
A model he and colleagues created shows how, if lockdowns are lifted, a second peak will spring up like a released rubber band. But that same model shows a much smaller, flatter second peak if people limit what he calls long-distance interactions.
If you can distinguish long-distance ties from closer-community ties and allow the community activity to go on, he says, you can reduce the speed of future spread by orders of magnitude. People are hung up on how big gatherings should be, he said, but it matters even more who is gathering. A regular church service with the same community members won’t cause the same problem as an international business conference, or a county fair, where strangers rub elbows.
He likens this to shutting down “highways of transmission,” and forcing the virus to travel through slower side streets.
Network science, too, may help explain the patchy distribution of the virus. Experts are struggling to find reasons why the disease is more prevalent in some states, some cities and even some neighborhoods within those cities.
The virus will form geographic clumps on scales big and small independent of policy and behavior, Van de Rijt says. It’s a product of its exponential spread. If, in the early stages, a couple of extra cases cluster in one region, those few seeds can grow a big outbreak. And that adds a level of challenge to evaluating strategies of different states and countries. There’s an element of chance mixed in.
Smarts, skepticism or politics: What determines your fear of Covid-19?
Covid-19 is puzzling not just in the wide range of symptoms it produces but in the wildly divergent attitudes it’s inspired. Why are some people terrified, while others with similar risk factors not afraid at all? Why are some more afraid of economic collapse than germs? Is this diversity of feeling being driven by people’s media diets and political views, as with climate change? Or perhaps, as many pundits insist, it’s a matter of intelligence because there’s a right answer and those with well-functioning brains have figured it out.
Social scientists David Rand of Yale and Gordon Pennycook of the University of Regina in Canada investigated by gathering data on people’s Covid-19 risk perception, as well as their political leanings, media preferences and something they called “cognitive sophistication.” The latter included measures of numeracy, science literacy and a test of analytic ability called the cognitive reflection test, as well as a sort of gullibility measure called the “bullshit receptivity test.”
The survey included more than 1,800 people from the U.K., U.S. and Canada. The results are posted on a preprint server here. (These are not yet peer reviewed, but Rand and Pennycook have been published many times in the major scientific journals and have not steered me wrong yet.)
The result: Political affiliation did affect attitudes, with conservatives less likely to be afraid than liberals. That might seem obvious, but during the 2014 Ebola outbreak, it was the conservatives calling to quarantine doctors returning from trips to Africa to care for victims. And previous studies had made the claim that conservatives are naturally more fearful than liberals — results that were controversial but widely embraced by people on the liberal end of the spectrum.
The contention is more dubious than ever now. Fear is certainly politicized, but only because conservatives and liberals are likely to be afraid of different things.
The researchers also tried to understand the role of misperceptions about Covid-19, though it may be too early to study these, as much of the accepted wisdom changes by the day. They included an item about pets getting the disease, which they categorized as a misconception, but the latest news suggests it might be a real risk. Overall, the misconceptions were divided into pessimistic (playing up the threat), optimistic (playing down the threat), and conspiracy related, such as the idea that the virus was created in a lab. That conspiracy theory was most popular in the United States, where 13% reported they believed it.
And what about those scores of cognitive sophistication? They did predict how resistant people were to misconceptions, but there was no connection between those tests and fear.
The more analytical, skeptical, numerate, science-literate people were no more likely to be afraid of the disease, or more willing to change their behavior.
And that all makes sense. Some people are naturally more risk averse, more germ phobic, and more freaked out about death – which wouldn’t seem to have much to do with smarts or skepticism. Fear is an emotion — an instinct, and there’s no right answer about when to feel it.
Iceland’s data and the debate over Covid-19 prevalence
Keep your eyes on Iceland. Researchers there have some experience collecting good medical data. A biopharmaceutical company called deCODE genetics, recently acquired by Amgen, has switched gears from studying the genetic underpinnings of diabetes, heart disease and mental illness to focus on decoding the genes of SARS-CoV-2 viruses.
While most testing worldwide is done only for people who have severe symptoms, the company has conducted a rare random sampling of the population to get a handle on how widespread the disease had become. The prevalence infection is still a point of contention, since early reports out of China suggested a high death rate — more than 1% — and lower transmissibility. Other studies, including a recent one from Stanford University which sampled Covid-19 antibodies in Silicon Valley residents, indicated the virus was much more common and therefore much more transmissible but a lot less deadly.
deCODE is also sequencing the genes of the viruses collected from volunteers, which reveal mutations that can act like a return address, helping researchers trace paths of infection.
They published results in the New England Journal of Medicine last week.
“We started screening people January 31,” said deCODE founder Kari Stefansson. That was well before the first official cases, which were tied to people returning from ski vacations in the Italian and Austrian Alps.
The virus has been accumulating different mutations since it broke out in China, he says, branching out in different lineages. The mutations in Icelanders’ viruses pointed to additional spread from the UK, where scientists now realize the virus was much more widespread than people had realized.
Among Icelanders, the random sampling of 2,283 people revealed a few hidden infections. 13 people, or 0.6%, tested positive. A number of people in the random group reported some recent coughs and other cold-type symptoms. In another group of “high risk” patients with typical coronavirus symptoms, 13.2% tested positive. Stefansson says they plan to follow the random group to find out if anyone developed a truly asymptomatic course of the disease.
Children were less likely than adults to test positive. And there was not a single case of children spreading the virus to their parents. The testing also offered clues to still-unexplained sex differences — women are not only less likely to die from the virus, in Iceland they were less likely to test positive in the first place.
The next step will be to test people for antibodies, which indicate an ongoing or past infection, and so can reveal where the virus has already been. The Stanford study tested people for antibodies, but it generated some controversy over the test accuracy and statistical methods. DeCode’s Stefansson said they are waiting to make sure they understand the accuracy of their tests before releasing results.
One of the big questions deCode could help answer is why some people become extremely sick and others don’t. This variability in virulence might have something to do with differences in the genetics of the viruses, or in the genetics of the humans who get sick, Stefansson said. Beyond that, the severity of symptoms may depend on whether people had recently been infected with other coronaviruses in circulation, which are associated with the common cold.
So far, while Iceland has encouraged social distancing, they have not closed shops or elementary schools. And yet, they’ve had only 10 people die from Covid-19 — a per-capita rate that’s less than a quarter of that in the United States. The secret of their success, said Stefansson: testing.
This column does not necessarily reflect the opinion of the editorial board or Bloomberg LP and its owners.
Faye Flam is a Bloomberg Opinion columnist. She has written for the Economist, the New York Times, the Washington Post, Psychology Today, Science and other publications. She has a degree in geophysics from the California Institute of Technology.
For more articles like this, please visit us at bloomberg.com/opinion
Subscribe now to stay ahead with the most trusted business news source.
©2020 Bloomberg L.P.