Excellence in Research: Bending the Curve for Vulnerable Populations: A Data-Analytical and Socio-Technical Decision-Making Framework forSheltering in Hurricane-Pandemics

地球物理灾害与COVID-19大流行同时发生，以独特的方式挑战了最脆弱人群的复原力。在大流行病期间，飓风等自然灾害除了对身体和社会脆弱性机制产生复合影响外，还对大众保健资源造成额外压力。由于社交距离的要求，常规收容所空间的容量将大幅减少，可能需要考虑其他非聚集性收容所，如旅馆/汽车旅馆或翻新设施。该卓越研究（EiR）项目采用社区参与的多学科方法，以解决同时发生的飓风和流行病的紧迫研究问题，重点关注弱势群体面临的挑战。 该项目的总体目标是制定一个新的数据分析框架，将流行病学模型与飓风管理办法结合起来，并对社会脆弱性有深入的了解。该框架可以帮助公共卫生和应急管理人员做出避难和资源分配决策，同时最大限度地减少疾病传播。该研究团队汇集了来自工程和社会科学的研究人员，他们在统计学习，基础设施恢复力，灾害风险分析和社会脆弱性方面具有专业知识，以便系统地研究研究问题。该项目旨在通过提高脆弱社区在飓风大流行中的复原力，解决国家在备灾方面的关键需求，并促进国家健康、繁荣和福利。研究活动将包括调查统计疾病传播和疫情检测方法，将流行病模型与飓风后送情景分析相结合，以更好地预测疾病传播并在飓风后分配资源。飓风大流行病，以及通过调查和重点小组让应急管理人员和社会工作者参与脆弱性分析。 具体而言，项目组将采用以下方法：（1）风险调整的公共卫生监测方法，以制定针对性的流行病遏制和脆弱人群的庇护计划，（2）基于网络的流行病模型，以了解在庇护行动期间人口混合如何影响疾病传播，并预测新感染的规模和时间，（3）网络阻断模型，以探讨流行病引起的破坏对地理上分散的避难所的影响，并确定应对新出现的疾病爆发的避难所和资源分配的最佳分配，以及（4）在利益攸关方的积极参与下，采用综合的定性和定量方法，收集关于弱势群体需求的关键信息，并确定脆弱性指标特别是飓风大流行。此外，该研究将有助于多学科教育和技术培训的代表性不足的少数民族学生和生产高等学位HBCU毕业生更好地准备进入劳动力市场。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

Co-occurrence of geophysical hazards with the COVID-19 pandemic has challenged the resilience of the most vulnerable populations in unique ways. In the midst of a pandemic, a natural disaster such as a hurricane puts additional strain on mass care resources in addition to the compounding effects of the two hazards on the mechanisms of physical and social vulnerability. As a result of social distancing requirements, the capacities of regular shelter spaces will be reduced drastically and alternate non-congregate shelters— such as hotel/motels or renovated facilities— may need to be considered. This Excellence in Research (EiR) project takes a community-engaged, multidisciplinary approach to address the pressing research problems for concurrently occurring hurricanes and pandemics, with a focus on the challenges facing vulnerable populations. The overall objective of the project is to formulate a new data-analytical framework that integrates epidemiological models with hurricane management approaches with a strong understanding of social vulnerabilities. This framework can help public health and emergency managers make sheltering and resource allocation decisions while simultaneously minimizing the disease spread. The research team brings together investigators from engineering and social science with expertise in statistical learning, infrastructure resilience, disaster risk analysis, and social vulnerability in order to systematically study the research problems. By improving the resilience of vulnerable communities in hurricane-pandemics, the project aims to address a critical national need in disaster preparedness as well as advance national health, prosperity, and welfare.The research activities will include investigation of statistical disease spread and outbreak detection methods, integration of epidemic models with hurricane evacuation scenario analyses to better predict disease spread and allocate resources in the aftermath of hurricane-pandemics, and engagement of emergency managers and social workers in vulnerability analysis through surveys and focus groups. Specifically, the project team will utilize the following methods: (1) risk-adjusted public health surveillance methods to devise targeted pandemic containment and sheltering plans of vulnerable populations, (2) network-based epidemic models to understand how mixing of populations during sheltering operations affect disease transmissions and to make forecasts of the size and timing of new infections, (3) network interdiction models to explore the impacts of pandemic-induced disruptions on geographically dispersed shelters and to determine the optimal assignments of shelters and resource allocations in response to emerging disease outbreaks, and (4) integrated qualitative and quantitative methods with active stakeholder participation to gather key information on the needs of vulnerable groups and enable definition of vulnerability indicators specific to hurricane-pandemics. Furthermore, the research will contribute to the multi-disciplinary education and technical training of under-represented minority students and producing advanced-degree HBCU graduates better prepared to enter the workforce.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.