Why is it difficult to predict the next step of the pandemic


But it is also a constant change of frustration and fatigue, a drastic alternation between pessimism and optimism, such as last fall, when Americans returned to vacation travel during the most severe surge of the epidemic. Now, although the summer peak is as bad as ever, in many parts of the country, society has basically returned to normal. “During an ongoing pandemic, people will dramatically change their behavior,” Bergstrom said. “We are constantly updating our views on how serious this matter is.”

In some ways, this means that more pandemic experience can create more Uncertainty for the modeler, not less. Beliefs and behaviors are now increasingly diverse, varying from state to state, and in some cases from town to town. Delta has arrived and people have become more polarized after vaccination and are confused about what this means for their behavior. “It’s okay to wear a mask for one month, but it’s a protest next month. It’s really hard to predict in advance,” Gakidou said.

Joshua Weitz, a professor of complex biological systems at the Georgia Institute of Technology, said: “The popular themes that continue to make things difficult now are the interaction between disease states, people’s reactions, and how people respond over time.” Eighteen months after the pandemic, it was a very intuitive idea that our personal perceptions of risk and the subsequent behaviors should have a collective impact on the trajectory of the virus. But this was not a common understanding at the beginning. Weitz pointed out that at the time some people thought the pandemic would pass soon. In terms of modeling, this term (a relic of the 19th-century epidemiological theory) is Farr’s law: infection should peak at a relatively equal rate and then weaken, resulting in a bell curve.

This curve will not obey. Last spring, Weitz and others could see it return in the second round. The first wave has not been completely defeated, and there are still too many people who are susceptible. The number of cases reached a peak, and then was trapped on the “shoulder” of the curve, falling slower than many predictions suggest, and then stagnating with a stubbornly high infection rate. Weitz hypothesized that behavior is inconsistent with the effects of interventions such as stay-at-home orders predicted by the model. By studying mobility reports (representatives of how much social contact people are experiencing) extracted from mobile phone data, he can see that as the death toll rises, dangerous behaviors decrease, but they start to rebound before turning. “People look around, look at the local situation, and then they change their behavior,” Weitz said.

One consequence of these reactive behaviors is that it is difficult to analyze how helpful policies such as masks and vaccine injunctions are. There is ambiguity between causality, ambiguity between government actions and what the public is already doing, because both respond to the rise and fall of transmission rates. For example, he said, if you look at the time of the mask enforcement order in Georgia last year and compare the before and after case rates, you might be sure that it has little effect. But what if it is because people realize that the case rate is rising and wear masks in advance? What if they start to stay at home more? Or what if the other way around: the requirements are in effect, and few people follow the rules, so masks never have a chance to work? “There is obviously a relationship,” he said. “I can’t claim that we have found the bottom of it.”

For modelers, this uncertainty is a challenge. In order to assess when the delta wave is over, one might look at places where it has soared and reached its peak, such as the United Kingdom. But will it disappear soon, or will it gradually decrease, or may it remain stable with a stable infection rate? Weitz believes that these scenarios will largely depend on how people view risks and behaviors. Delta variants are expected to hit differently in high vaccination and eventually fade Vermont When the vaccination rate is lower AlabamaThe different policies of schools and enterprises will determine how much the number of different groups will be mixed, and will be amplified or weakened by people’s independent reactions.


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