The US COVID-19 and Influenza Scenario Modeling Hubs: Delivering long-term projections to guide policy

IF 3 3区 医学 Q2 INFECTIOUS DISEASES Epidemics Pub Date : 2023-12-29 DOI:10.1016/j.epidem.2023.100738
Sara L. Loo , Emily Howerton , Lucie Contamin , Claire P. Smith , Rebecca K. Borchering , Luke C. Mullany , Samantha Bents , Erica Carcelen , Sung-mok Jung , Tiffany Bogich , Willem G. van Panhuis , Jessica Kerr , Jessi Espino , Katie Yan , Harry Hochheiser , Michael C. Runge , Katriona Shea , Justin Lessler , Cécile Viboud , Shaun Truelove
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Abstract

Between December 2020 and April 2023, the COVID-19 Scenario Modeling Hub (SMH) generated operational multi-month projections of COVID-19 burden in the US to guide pandemic planning and decision-making in the context of high uncertainty. This effort was born out of an attempt to coordinate, synthesize and effectively use the unprecedented amount of predictive modeling that emerged throughout the COVID-19 pandemic. Here we describe the history of this massive collective research effort, the process of convening and maintaining an open modeling hub active over multiple years, and attempt to provide a blueprint for future efforts. We detail the process of generating 17 rounds of scenarios and projections at different stages of the COVID-19 pandemic, and disseminating results to the public health community and lay public. We also highlight how SMH was expanded to generate influenza projections during the 2022–23 season. We identify key impacts of SMH results on public health and draw lessons to improve future collaborative modeling efforts, research on scenario projections, and the interface between models and policy.

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美国 COVID-19 和流感情景建模中心:为指导政策提供长期预测
2020 年 12 月至 2023 年 4 月期间,COVID-19 情景建模中心(SMH)对美国的 COVID-19 负担进行了多月预测,以在高度不确定的情况下指导大流行规划和决策。这项工作是为了协调、综合和有效利用在 COVID-19 大流行期间出现的前所未有的大量预测建模工作。在此,我们描述了这一大规模集体研究工作的历史、召集和维护一个活跃多年的开放式建模中心的过程,并试图为未来的工作提供一个蓝图。我们详细介绍了在 COVID-19 大流行的不同阶段生成 17 轮情景和预测的过程,以及向公共卫生界和普通公众传播结果的过程。我们还重点介绍了如何将SMH扩展到2022-23流感季节的流感预测。我们确定了 SMH 结果对公共卫生的主要影响,并总结了经验教训,以改进未来的合作建模工作、情景预测研究以及模型与政策之间的衔接。
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来源期刊
Epidemics
Epidemics INFECTIOUS DISEASES-
CiteScore
6.00
自引率
7.90%
发文量
92
审稿时长
140 days
期刊介绍: Epidemics publishes papers on infectious disease dynamics in the broadest sense. Its scope covers both within-host dynamics of infectious agents and dynamics at the population level, particularly the interaction between the two. Areas of emphasis include: spread, transmission, persistence, implications and population dynamics of infectious diseases; population and public health as well as policy aspects of control and prevention; dynamics at the individual level; interaction with the environment, ecology and evolution of infectious diseases, as well as population genetics of infectious agents.
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