FatCool schreef op 17 augustus 2020 12:57:
Covid Spread Can’t Only Be Explained by Who’s Being ‘Bad’(Bloomberg Opinion) -- There are some weird things going on in the coronavirus data. It’s curious that cases dropped so fast, and have stayed pretty low, in the spring hot zones — New York, New Jersey and Connecticut. And why did cases remain so low in Idaho and Hawaii until recently?
The mainstream narrative is that it’s all about good behavior when cases go down — mask wearing and giving up our social lives for the greater good. And conversely, bad behavior must be what makes them go up. We talk about certain regions having the virus “under control,” as if falling cases are purely a matter of will-power. A sort of moral reasoning is filling in for evidence.
But why, then, have cases plummeted in Sweden, where mask wearing is a rarity?
This is the time to use scientific methods to understand what’s happening. The pandemic has gone on long enough to reveal patterns in the way it spreads. If it’s all about behavior, that’s a testable hypothesis. If, as a few speculate, dramatic drops in some places have something to do with growing immunity in the population, we can also turn that into a testable hypothesis.
“The issue with data is one can manipulate it to show anything you want if you have an agenda,” says YouYang Gu, an independent data scientist. Cherry picking is easy — prediction is much harder, and Gu is getting some attention for the fact that models he’s been creating since April actually forecast what’s happened with the spread of the disease in the U.S.
He recently took to Twitter to urge public health officials to apply scientific thinking. He pointed to data on Louisiana, where cases were rising earlier in the summer and seemed to level off after various counties issued mask mandates.
But breaking the data down by county, he says, revealed a different story. Mask mandates varied in their timing, but places that implemented them late saw no more cases or deaths than those that did so early. “I don’t think there’s currently enough evidence to support the fact that recent policy interventions (mask mandates, bar closures) were the main drivers behind the recent decrease in cases,” he wrote.
That’s not to say that individual behavior doesn’t matter a lot — and the cancellation of big gatherings and other potential super-spreading events is more important than ever — but there may be more factors than we know driving the bigger picture.
A few scientists are examining the possibility that previously hard-hit areas are now being affected by a buildup of immunity, even if it flies in the face of the widespread understanding that the disease has to run through at least 60% of the population to achieve so-called herd immunity. (So far, antibody tests show only some 10-20% of the U.S. population has had the disease.)
The term herd immunity is a little vague in this context. It was created to characterize the impact of immunization. It refers to the percentage of the population that must get immunized in order for a pathogen to die out — a quantity that depends on the nature of the virus, the efficacy of the vaccine and the behavior of the hosts. If natural immunity is starting to help in some places, that would suggest herd immunity is a reasonable and worthy goal of an immunization program.
But scientists have little experience applying herd immunity to a natural infection, and what understanding they have is changing. Scientists have started to investigate the possibility that there’s another critical factor here — heterogeneity in the way humans interact, and in our inherent, biological susceptibility to this disease.
In a Science paper published in June, University of Stockholm mathematician Tom Britton and colleagues calculated that herd immunity might be reached after as few as 43% of a very heterogenous population becomes infected. People mix unevenly in a way that could lead to little pockets of immunity, slowing the spread of the virus long before the world achieves herd immunity.
We may also be heterogeneous in our biology. A recent paper in Science suggests that many people who’ve never been infected with SARS-CoV-2 carry a kind of immune cell, called a T-cell, which recognizes this novel virus and may partially mitigate an infection. These cells may be left over from infections with related viruses — the coronaviruses that cause the common cold.
While scientists who authored the paper warn that it doesn’t imply that people with pre-existing T-cells can’t get infected, they leave open the possibility that it might account for some of the vast variability in symptoms.
Whatever the source of this heterogeneity, we know it exists. Most people on the contaminated cruise ship Diamond Princess remained uninfected, while others got asymptomatic infections and still others got severely ill.
Those differences can inform disease models, says statistics professor Gabriela Gomes of the University of Strathclyde in Scotland. “What we see is that infections do not occur at random, but that people who are most susceptible to infection get exposed first,” she says, leaving a pool of ever-less susceptible people behind.
So far, her predictions of the spread in the U.K., Belgium, Spain and Portugal have aligned well with reality. Her models showed small, shallow second peaks that would concentrate away from the places where the pandemic was most rampant last spring. For example, in Spain, the first outbreak was around Madrid, and now a smaller outbreak is happening around Catalonia.
www.msn.com/en-us/news/technology/cov...