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But it’s also a landscape of changing frustrations and fatigue, wild alternations between pessimism and optimism, like last fall when Americans returned to vacation travel in what was then the biggest jump in the pandemic. And now, despite the summer peak, which is as bad as it once was, in many parts of the country society is largely returning to business as usual. “People are drastically changing their behavior during an ongoing pandemic,” Bergstrom said. “We are constantly updating our beliefs about how serious this is.”
In a sense, this means that more pandemic experience can be created More ▼ uncertainty for modelers, no less. Beliefs and behaviors are now increasingly diverse, varying from country to country and in some cases from city to city. The delta arrived at a time when people are becoming increasingly polarized after vaccinations and are confused about what this means for how they should behave. “The mandates for a mask for one month are OK, and next month these are protests. It’s really hard to predict in advance, “Gakidou said.
“The predominant theme that continues to make things difficult now is the interaction between disease, how people react, and how people react over time,” said Joshua Weitz, a professor of complex biological systems at the Georgia Institute of Technology. It is a completely intuitive idea 18 months after the pandemic that our individual perceptions of risk and the behavior that follows from it should have a collective impact on the trajectory of the virus. But that was not the universal understanding in the beginning, Weitz noted, when some believed the pandemic would pass quickly. In model language, the term for this (a relic of 19th-century epidemic theory) is Farr’s law: Infections must peak and then decrease at a relatively steady rate, leading to a bell curve.
This curve would not obey. Last spring, Weitz and others could see him returning for the second round. The first wave was not completely crushed and too many people remained susceptible. Cases peaked, then crashed into the “shoulders” of the curve, declining at a slower pace than many predictions suggest, and then cried at persistently high levels of infection. The behavior, Weitz suggested, is out of sync with how the models envisage interventions such as orders to stay at home. By studying mobility reports derived from mobile phone data, an indicator of how many people are experiencing social contacts, he could see that risky behavior decreases with increasing deaths, but then begins to recover before turning. “People look around, they see the local situation and they change their behavior,” says Weitz.
One consequence of these reactive behaviors is that it can be difficult to analyze how useful policies such as masks and vaccines are. There is a blur between cause and effect – and between government action and what the public is already doing, as both respond to rising and falling transmission speeds. For example, he says, if you look at the timing of the mask mandate introduced in Georgia last year and compare the percentage of cases before and after, you can see that it has little effect. But what if it was because people realized that the cases were increasing and preventively put on their masks earlier? What if they just started staying home longer? Or what if it was the other way around: The requirement went into effect and few people followed the rules so the masks never had a chance to do their job? “There’s obviously a connection there,” he says. “I can’t say we’ve reached the bottom.”
For modelers, this uncertainty is a challenge. To assess when the Delta can end, one can look for places where it has already occurred and was at the top, such as the United Kingdom. But will it die quickly, or will it take up more slowly, or perhaps a plateau with a constant rate of infection? These scenarios, Weitz argues, will largely depend on how people perceive risk and behave. The Delta option is expected to strike and eventually withdraw differently in Vermont with high vaccination than in low-vaccinated Alabama. Different policies for schools and businesses will determine how many people from different groups will mix and be reinforced or undermined by how people react independently.
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