The Omicron wave is the largest wave of COVID-19 pandemic to date, more than doubling any other in terms of cases and hospitalizations in the United States. In this paper, a large-scale agent-based model of policy interventions that could have been implemented to mitigate the Omicron wave is presented. The model takes into account the behaviors of individuals and their interactions with one another within a nationally representative population, as well as the efficacy of various interventions such as social distancing, mask wearing, testing, tracing, and vaccination. We use the model to simulate the impact of different policy scenarios and evaluate their potential effectiveness in controlling the spread of the virus. The results suggest the Omicron wave could have been substantially curtailed via a combination of interventions comparable in effectiveness to extreme and unpopular singular measures such as widespread closure of schools and workplaces, and highlight the importance of early and decisive action.

中文翻译：

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TRACE-Omicron：政策反事实为缓解美国 COVID-19 传播提供信息

Omicron 浪潮是迄今为止最大规模的 COVID-19 大流行浪潮，就美国的病例数和住院人数而言，是其他浪潮的两倍多。本文提出了一种基于代理的大规模政策干预模型，可以用来缓解 Omicron 浪潮。该模型考虑了全国代表性人群中个人的行为及其相互之间的互动，以及社交距离、戴口罩、检测、追踪和疫苗接种等各种干预措施的效果。我们使用该模型来模拟不同政策情景的影响，并评估其在控制病毒传播方面的潜在有效性。