Covid spread can’t only be explained by who’s being ‘bad’

There are some weird things going on in the coronavirus data. ,t’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 ,daho 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 ³under 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 plummet ed in Sweden, where mask wearing is a rarity"

This is the time to use scientific meth ods to understand what’s happening. The pandemic has gone on long enough to reveal patterns in the way it spreads. ,f it’s all about behavior, that’s a testable hypothesis. ,f, as a few speculate, dra matic drops in some places have some thing to do with growing immunity in the population, we can also turn that into a testable hypothesis.

³The issue with data is one can manip ulate it to show anything you want if you have an agenda,” says YouYang Gu, an independent data scientist. Cherry pick ing 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 8.S.

He recently took to Twitter to urge public health officials to apply scientific thinking. He pointed to data on /ouisi ana, 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 coun ty, 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. ³, 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 be havior 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 8.S. popula tion has had the disease.

The term herd immunity is a little vague in this context. ,t was created to characterize the impact of immunization. ,t refers to the percentage of the popu lation that must get immunized in order for a pathogen to die out – a Tuantity that depends on the nature of the virus, the ef ficacy of the vaccine and the behavior of the hosts. ,f natural immunity is starting to help in some places, that would sug gest herd immunity is a reasonable and worthy goal of an immunization pro gram.

But scientists have little experience applying herd immunity to a natural in fection, and what understanding they have is changing. Scientists have started to investigate the possibility that there’s another critical factor here – heterogene ity in the way humans interact, and in our inherent, biological susceptibility to this disease.

,n a Science paper published in June, 8niversity of Stockholm mathematician Tom Britton and colleagues calculated that herd immunity might be reached af ter as few as 43% of a very heterogenous population becomes infected. 3eople 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 sug gests that many people who’ve never been infected with SA5S Co9 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 infec tions with related viruses – the coronavi ruses that cause the common cold.

While scientists who authored the pa per warn that it doesn’t imply that people with pre existing T cells can’t get infect ed, they leave open the possibility that it might account for some of the vast vari ability in symptoms.

Whatever the source of this heteroge neity, we know it exists. Most people on the contaminated cruise ship 'iamond 3rincess remained uninfected, while oth ers got asymptomatic infections and still others got severely ill.

Those differences can inform disease models, says statistics professor Gabriela Gomes of the 8niversity of Strathclyde in Scotland. ³What we see is that infec tions do not occur at random, but that people who are most susceptible to in fection get exposed first,” she says, leav ing a pool of ever less susceptible people behind.

So far, her predictions of the spread in the 8..., Belgium, Spain and 3ortu gal 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.

She says her models keep predicting declines after the infection reached be tween 10% and 35% of the population. That doesn’t mean the virus has gone away – only that by her models, it won’t explode in those same places again. Gu’s models, too, predict no big second waves in New York City or Stockholm, but leave open the possibility of new out breaks in relatively unaffected areas, just as Hawaii is now fighting outbreaks and New Zealand has imposed a new, short lockdown.

She says she didn’t expect to come up against resistance to her models in the scientific community. While she’s start ing to get some attention in the media, she said journal editors told her that her modeling ideas, in preprint, posed the danger of making people feel entitled to relax their vigilance. Maybe the opposite is true, she suggests. Maybe censoring all but the most pessimistic views could dis courage action by making the problem seem endless.

The controversy mirrors one that took place a few years ago when renowned cancer researcher Bert 9ogelstein dared to suggest that the very nature of can cer had a random element and therefore some people who did everything right would get cancer through bad luck. He was pilloried for the view, not because it was untrue, but because it was deemed a dangerous invitation for people to be bad.

3ublic health in the 8nited States has a tendency toward moralizing against indulgences. We were told obesity was caused by indulgence in high fat food even though the evidence pointed else where, and it took years to recognize that opioid addiction is a disease and not a sin. That attitude may be ingrained in the culture, but it shouldn’t get in the way of the search for the truth.