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

在当今世界，几乎不需要说明流行病对社会的致命和破坏性，以及了解和预测流行病在时间和空间上的演变是多么重要。值得注意的是，大流行的严重程度对社区的影响是不同的，往往在服务不足和与世隔绝的社区造成更大的死亡率。例如，几十年来，在不同类型的流行病中，包括目前的新冠肺炎大流行，土著居民的死亡率是普通公众的三倍多。该研究小组旨在通过在与世隔绝和服务不足的人群中增进关于大流行动态的知识，为全球大流行预测和预防做出贡献。具体地说，调查人员研究传染病大流行如何影响其在土著社区的传播，并受到其影响。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、病原体在人与人之间的传播、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Potawatomi部落的成员，并与外部合作伙伴联系。团队会议作为团队科学研究的观察数据，学生培训和指导活动提供了与下一代研究人员沟通的机会。研究人员确定了三个主要问题，它们激励着四个具体的研究推动力：(1)什么因素，从环境到分子，对土著社区的死亡率有贡献？(2)这项研究的结果能否转化为对流行病动力学的更广泛理解？(3)可以设计出什么工程、教育、生物和政策解决方案来解决问题的根本原因？该项目最初将重点放在流感上，尽管预计这些发现也将适用于其他病毒性疾病，如新冠肺炎、埃博拉和寨卡病毒。为了解决这些主要问题，该项目将在工程学、生物学、数据科学和认知心理学领域沿着四个相互关联的方向进行合作创新：(I)社区对原因和预防的理解，这将在土著社区中建立关于疾病及其改善的信念。研究人员将采用基于社区的参与性研究(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，这将把灾难和网络建模方面的计算、统计和数据科学专业知识应用于预测孤立社区的动态。(3)护理点感测工程设备，该设备将开发敏感和简化的工具，以加强服务不足的土著人口的检测能力，并改进对流行病的跟踪。(4)生物分化因素：预测感染，这将调查病毒与宿主细胞的相互作用，以及表型和基因分化因素。这一奖项由跨部门的大流行预防第一阶段预测情报(PIPP)计划支持，该计划由生物科学(BIO)、计算机信息科学和工程(CEISE)、工程(ENG)和社会、行为和经济科学(SBE)局长共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.