Thompson School of Social Work & Public Health, University of Hawaii at Manoa, Honolulu, HI 96822, USA.
Hawaii Data Collaborative, Honolulu, HI 96813, USA.
Int J Environ Res Public Health. 2022 May 18;19(10):6119. doi: 10.3390/ijerph19106119.
In the face of great uncertainty and a global crisis from COVID-19, mathematical and epidemiologic COVID-19 models proliferated during the pandemic. Yet, many models were not created with the explicit audience of policymakers, the intention of informing specific scenarios, or explicit communication of assumptions, limitations, and complexities. This study presents a case study of the roles, uses, and approaches to COVID-19 modeling and forecasting in one state jurisdiction in the United States. Based on an account of the historical real-world events through lived experiences, we first examine the specific modeling considerations used to inform policy decisions. Then, we review the real-world policy use cases and key decisions that were informed by modeling during the pandemic including the role of modeling in informing planning for hospital capacity, isolation and quarantine facilities, and broad public communication. Key lessons are examined through the real-world application of modeling, noting the importance of locally tailored models, the role of a scientific and technical advisory group, and the challenges of communicating technical considerations to a public audience.
面对 COVID-19 带来的巨大不确定性和全球危机,数学和流行病学 COVID-19 模型在疫情期间大量涌现。然而,许多模型并非专为决策者设计,也并非旨在提供具体场景,或明确说明假设、局限性和复杂性。本研究以美国一个州的司法管辖区为例,探讨了 COVID-19 建模和预测的作用、用途和方法。基于对现实世界历史事件的亲身体验的描述,我们首先考察了用于为政策决策提供信息的具体建模考虑因素。然后,我们回顾了在疫情期间建模所支持的现实世界政策用例和关键决策,包括建模在为医院容量、隔离和检疫设施以及广泛的公众沟通规划提供信息方面的作用。通过对建模的实际应用进行了考察,探讨了关键经验教训,指出了定制化模型的重要性、科学和技术咨询小组的作用,以及向公众传达技术考虑因素的挑战。