PIPP Phase I: Transdisciplinary Innovation in Predictive Science for Emerging Infectious Disease and Spillover

PIPP 第一阶段：新发传染病和溢出预测科学的跨学科创新

• 批准号: 2200221
• 负责人: Christine Johnson
• 金额: $ 99.98万
• 依托单位: University of California-Davis
• 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 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2200221&HistoricalAwards=false
• 关键词: PIPP; Phase; Transdisciplinary; Innovation; Predictive

The scale and impact of epidemics and pandemics are expected to increase substantively in future years given global trends in environmental change. Pandemics are most often caused by spillover events in which viruses from wild animals jump to people and spread, quickly outpacing containment efforts. Pandemics are best contained at the earliest stages of emergence, yet major hurdles have stood in the way of early detection of pandemic threats at the scale that is needed. We set forth an ambitious scientific agenda to overcome technological limitations impeding detection and characterization of emerging pandemic threats. Our team spanning engineering, computer science, social science, epidemiology, and virology with stakeholders from public health, wildlife health, and industry is first-of-a-kind to advance predictive intelligence for potential pandemics. We will develop new disease surveillance technologies that incorporate innovative sensing, epidemiological insights, and artificial intelligence strategies, to detect what animals are present and what viruses they carry - all remotely with little human intervention. We seek to develop diverse, inclusive, and highly functional transdisciplinary research teams and trainees, to move beyond the state of the art in predictive intelligence for pandemics to inform national and global health security. We address the grand challenge of generating actionable intelligence for early detection of pandemic threats at the point of disease spillover from animals to people. We are planning a transdisciplinary center and associated research to advance our ability to characterize environmental change and animal-human interactions that facilitate the emergence of pandemic threats, and develop predictive capabilities in forecasting pandemic risk, to enable an evidence-base that can inform pandemic prevention. Research advances will be focused on 1) characterizing environmental conditions and the human dimensions of disease emergence, especially the animal and human movements, networks, and social systems that facilitate spillover at the animal-human interface, 2) inventing broad-spectrum sensor technologies for rapid, accurate, safe, and scalable pathogen detection tailored to a range of animals in diverse environments, and 3) improving forecasting by integration of epidemiologic and landscape data with machine learning to advance predictive intelligence. Our team will foster the convergence of creative ideas, novel approaches and technologies, transdisciplinary collaboration and communication, participatory community science, and cross-training for innovation for a profoundly diverse workforce.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.

鉴于环境变化的全球趋势，预计流行病和流行病的规模和影响将大大增加。大流行者通常是由溢出事件引起的，在溢出事件中，野生动物的病毒跳到人们并传播，迅速超越了遏制工作。 Pandemics最好在出现的最早阶段中包含，但主要的障碍却妨碍了需要在需要的规模上发现大流行威胁的方式。我们提出了一个雄心勃勃的科学议程，以克服技术局限性，阻碍了新兴大流行威胁的检测和表征。我们的团队涵盖工程，计算机科学，社会科学，流行病学和病毒学，与公共卫生，野生动植物健康和行业的利益相关者是首个促进潜在大流行病的预测智能。我们将开发新的疾病监视技术，这些技术结合了创新的感知，流行病学见解和人工智能策略，以检测到存在的动物以及它们所携带的病毒 - 几乎没有人为干预。我们寻求发展多样化，包容和高度功能的跨学科研究团队和受训者，以超越Pandemics的预测情报状态，以告知国家和全球卫生安全。我们应对在动物到人的疾病溢出点提早发现大流行威胁的巨大挑战。我们正在计划一个跨学科中心和相关的研究，以提高我们表征环境变化和动物人类相互作用的能力，以促进大流行威胁的出现，并在预测大流行风险方面发展预测能力，以实现可以为大流行预防的循证基础。研究进步将集中于1）表征环境状况以及疾病出现的人类层面，尤其是动物和人类运动，网络和社会系统，促进促进动物人类界面溢出的溢出，2）发明广泛的传感传感器技术，以快速，准确，准确，准确，安全，安全的病原体在各种环境中的范围，以及在各种环境中的范围，以及3）的范围。使用机器学习来提高预测智能的景观数据。我们的团队将促进创意，新颖的方法和技术，跨学科的合作与沟通，参与性社区科学以及跨培训的创新，以获得深远的劳动力的创新。这一奖项得到了跨领域预测智能的支持，该奖项是pandporication for pandemic for partepention opepention阶段I（PIPP）计划（PIPP），该计划是共同资助的，该计划是由Sciences（Bio）提供的。计算机，信息科学与工程（CISE）；工程（ENG）以及社会，行为和经济科学（SBE）。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评论标准来通过评估来支持的。

项目成果

Do honey badgers and greater honeyguide birds cooperate to access bees' nests? Ecological evidence and honey‐hunter accounts

蜜獾和更大的导蜜鸟会合作进入蜂巢吗？

• DOI: 10.1111/jzo.13093
• 发表时间: 2023
• 期刊: Journal of Zoology
• 影响因子: 2
• 作者: van der Wal, J. E. M.;Afan, A. I.;Anyawire, M.;Begg, C. M.;Begg, K. S.;Dabo, G. A.;Gedi, I. I.;Harris, J. A.;Isack, H. A.;Ibrahim, J. I.
• 通讯作者: Ibrahim, J. I.

A handheld electronic device with the potential to detect lung cancer biomarkers from exhaled breath

• DOI: 10.1007/s10544-022-00638-8
• 发表时间: 2022-12-01
• 期刊: BIOMEDICAL MICRODEVICES
• 影响因子: 2.8
• 作者: Emam, Shadi;Nasrollahpour, Mehdi;Sun, Nian-Xiang
• 通讯作者: Sun, Nian-Xiang