O'Gara David, Rosenblatt Samuel F, Hébert-Dufresne Laurent, Purcell Rob, Kasman Matt, Hammond Ross A
Division of Computational and Data Sciences, Washington University in St. Louis.
Vermont Complex Systems Center, University of Vermont.
Adv Theory Simul. 2023 Jul;6(7). doi: 10.1002/adts.202300147. Epub 2023 Apr 28.
The Omicron wave was 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, we present a large-scale agent-based model of policy interventions that could have been implemented to mitigate the Omicron wave. Our 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. Our 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.
奥密克戎浪潮是新冠疫情迄今为止规模最大的一波，在美国，其病例数和住院人数比其他任何一波都增加了一倍多。在本文中，我们展示了一个基于主体的大规模模型，该模型涉及为减轻奥密克戎浪潮本可实施的政策干预措施。我们的模型考虑了个体行为及其在具有全国代表性的人群中的相互作用，以及诸如社交距离、戴口罩、检测、追踪和疫苗接种等各种干预措施的效果。我们使用该模型模拟不同政策情景的影响，并评估它们在控制病毒传播方面的潜在有效性。我们的结果表明，通过采取一系列干预措施的组合，奥密克戎浪潮本可大幅缩减，这些干预措施的有效性堪比诸如广泛关闭学校和工作场所等极端且不受欢迎的单一措施，并凸显了早期果断行动的重要性。
