PIPP Phase I: Dynamics of Pandemic Spread and Prevention in Indigenous Communities

PIPP 第一阶段：原住民社区流行病传播和预防的动态

• 批准号: 2200066
• 负责人: Anand Jagota
• 金额: $ 99.99万
• 依托单位: Lehigh University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2025-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2200066&HistoricalAwards=false
• 关键词: PIPP; Phase; Dynamics; Pandemic; Spread

It hardly needs stating in today’s world how deadly and destructive to society pandemics can be, and how important it is to understand and predict the evolution of pandemics over time and space. Notably, the severity of pandemics impacts communities differently, often causing much greater mortality in underserved and isolated communities. For example, over the decades and across different types of epidemics, including the current COVID-19 pandemic, mortality rates among Indigenous populations have been more than three times that of the general public. This research team aims to contribute to global pandemic prediction and prevention by advancing knowledge about pandemic dynamics within isolated and underserved populations. Specifically, the investigators examine how pandemics of infectious disease affect and are affected by their spread in Indigenous communities. The focus will be on how specific features of these communities influence various aspects of epidemics, such as the initial spillover to humans, the human-to-human spread of the pathogen, the biological behavior of the pathogen, and countermeasures that can mitigate the impact of the disease. The assembled team is highly interdisciplinary, covering the broad scientific expertise, including members of the Cheyenne River Sioux and Prairie Band Potawatomi tribes, and connecting with external partners. Team meetings serve as observational data for a study of convergent team science, and student training and mentoring activities provide opportunities for bridging to the next generation of researchers.The investigators have identified three overarching questions that motivate four specific research thrusts: (1) What factors, environmental to molecular, contribute to the mortality rates in Indigenous communities? (2) Can the findings of this study translate to broader understanding of pandemic dynamics? (3) What engineering, education, biological, and policy solutions can be devised to address the root causes of the problems? The project initially focuses on Influenza, although it is expected that the findings will apply to other viral diseases such as COVID-19, EBOLA, and Zika. In order to address these overarching questions, the project will innovate collaboratively in the fields of engineering, biology, data science, and cognitive psychology along four interlinked thrusts: (I) Community Understanding of Cause and Prevention, which will establish the beliefs in Indigenous communities regarding disease and its amelioration. The investigators will employ a Community Based Participatory Research (CBPR) approach, which involves communities in all aspects of the research, so as to build trust between communities and researchers. (II) Predicting Virus Spillover and Spread, which will bring computational, statistical, and data science expertise in Catastrophe and Network Modeling to predicting dynamics in isolated communities. (III) Engineering Devices for Point-of-Care Sensing, which will develop sensitive and simplified tools to enhance testing capability in underserved Indigenous populations and improve pandemic tracking. (IV) Biological Differentiators: Predicting Infection, which will investigate virus-host cell interactions, and phenotypic and genotypic differentiators. This award is supported by the cross-directorate Predictive Intelligence for Pandemic Prevention Phase I (PIPP) program, which is jointly funded by the Directorates for Biological Sciences (BIO), Computer Information Science and Engineering (CISE), Engineering (ENG) and Social, Behavioral and Economic Sciences (SBE).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.

在当今世界，流行病对社会的致命性和破坏性是多么的大，理解和预测流行病随时间和空间的演变是多么的重要，这几乎不需要说明。 值得注意的是，大流行病的严重程度对社区的影响不同，在服务不足和孤立的社区，死亡率往往高得多。 例如，几十年来，在不同类型的流行病中，包括目前的COVID-19大流行病，原住民人口的死亡率是一般公众的三倍多。该研究小组的目标是通过提高对孤立和服务不足人群中流行病动态的认识，为全球流行病预测和预防做出贡献。具体而言，调查人员研究了传染病大流行如何影响土著社区及其传播的影响。重点将放在这些社区的具体特征如何影响流行病的各个方面，例如最初对人类的溢出，病原体的人际传播，病原体的生物学行为以及可以减轻疾病影响的对策。组建的团队是高度跨学科的，涵盖了广泛的科学专业知识，包括夏延河苏族和草原乐队波塔瓦托米部落的成员，并与外部合作伙伴联系。团队会议作为观察数据的研究收敛的团队科学，学生培训和指导活动提供了机会，桥接到下一代的researchers.The调查人员已经确定了三个首要问题，激发四个具体的研究主旨：（1）什么因素，环境分子，有助于土著社区的死亡率？(2)这项研究的结果能否转化为对流行病动态的更广泛理解？(3)可以设计哪些工程、教育、生物和政策解决方案来解决问题的根源？该项目最初侧重于流感，但预计研究结果将适用于其他病毒性疾病，如COVID-19，EBOLA和Zika。 为了解决这些首要问题，该项目将在工程，生物学，数据科学和认知心理学领域合作创新，沿着四个相互关联的主题：（I）社区对原因和预防的理解，这将建立土著社区对疾病及其改善的信念。研究人员将采用基于社区的前瞻性研究（CBPR）方法，让社区参与研究的各个方面，以便在社区和研究人员之间建立信任。(II)预测病毒溢出和传播，这将带来灾难和网络建模方面的计算，统计和数据科学专业知识，以预测孤立社区的动态。(III)护理点传感工程设备，将开发敏感和简化的工具，以提高服务不足的土著人口的检测能力，并改善大流行病跟踪。(IV)生物分化因子：预测感染，将研究病毒-宿主细胞相互作用，以及表型和基因型分化因子。该奖项得到了跨部门的大流行预防阶段预测情报（PIPP）计划的支持，该计划由生物科学（BIO），计算机信息科学与工程（CISE），工程（ENG）和社会部门共同资助。行为与经济科学（SBE）该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。