PIPP Phase I: Predicting and Preventing Epidemic to Pandemic Transitions

新冠肺炎大流行及其影响，无论是数百万人的生命损失，还是估计的数万亿美元损失，都是大流行病可能造成破坏的最近一个例子。在预测、早期发现和快速反应方面取得的任何明显进展都将对人类福祉产生重大影响。该项目的总体目标是为预测和预防未来的流行病制定一项全面的战略和所需的科学。在疫情出现前的人畜共患病阶段预测大流行，需要考虑被认为存在于哺乳动物和鸟类中的数百万种未描述的病毒，这可能会导致许多错误警报。另一方面，在大流行广泛传播后发现它已经为时已晚。取而代之的是，该项目将开发检测新出现的病原体何时从其自然动物储存库溢出到人类，导致小型、局部疾病集群的方法，并将寻求开发一套快速反应和缓解策略。研究议程将构成研究中心进行长期努力的基础。该项目为研究生和博士后提供教育和培训机会。这项研究围绕着从预测、检测到预防的自然过程中的四项任务展开。任务1寻求确定病原体出现的地点热点，并汇编最有可能导致最初暴发的人畜共患病病原体的排名表。任务2将侧重于利用适用于资源有限环境的方法检测医疗保健环境中的疾病异常，利用来自社交媒体、网络搜索、手机移动模式、本地病例报告和死亡报告的替代数据源。任务3将考虑引起局部疾病集群的病原体的更详细的特征。它还将开发基于网络的疾病传播模型，以预测当地疾病集群是否以及在何种条件下可能演变为大流行。任务4将侧重于缓解和应对战略，包括个人疗法和疫苗、全球治理问题以及以旅行限制、封锁、社会距离和戴口罩指令以及药物/疫苗资源分配等形式部署控制机制的决策工具。为了评估开发的框架，该团队将把它应用于最近的历史流行病和大流行，考虑到新冠肺炎、H1N1和埃博拉。研究团队跨越了一个巨大的多学科领域，包括生物学、生态学、流行病学、医学(传染病、病毒学和微生物学)、计算机与信息科学和。工程学和社会科学(行为科学、卫生政策和新兴媒体)。该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)、社会、行为和经济科学(SBE)和工程学(ENG)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价值和更广泛的影响审查标准进行评估，被认为值得支持。

The COVID-19 pandemic and its effects, both in terms of the millions of lives lost and the trillions in estimated costs, are a recent example of the devastation pandemics can cause. Any discernible progress in the prediction, early detection, and rapid response would have significant impacts on human welfare. The overarching goal of this project is to develop a comprehensive strategy and the required science for predicting and preventing future pandemics. Predicting a pandemic at its pre-emergence, zoonotic stage requires considering millions of undescribed viruses thought to exist in mammals and birds, which could lead to many false alarms. On the other hand, detecting a pandemic after it has spread widely is too late. Instead, this project will develop methods for detecting when an emerging pathogen has spilled over from its natural animal reservoir into humans, causing a small, localized disease cluster, and will seek to develop a suite of rapid response and mitigation strategies. The research agenda will form the basis of a research Center to undertake a longer-term effort. This project offers educational and training opportunities for graduate students and post-docs. The research is organized around four tasks that map to a natural progression from prediction and detection to prevention. Task 1 seeks to identify location hotspots of pathogen emergence and to compile ranked lists of the most likely zoonotic pathogens that could cause an initial outbreak. Task 2 will focus on detecting disease anomalies in healthcare settings with methods applicable to resource-limited settings, leveraging alternative data sources from social media, web search, cell phone mobility patterns, local case reports, and death reports. Task 3 will consider the more detailed characterization of a pathogen causing a local disease cluster. It will also develop network-based disease spread models to predict if, and under what conditions, the local disease cluster is likely to evolve into a pandemic. Task 4 will focus on mitigation and response strategies, including individual therapeutics and vaccines, issues of global governance, and decision-making tools to deploy control mechanisms in the form of travel restrictions, lockdowns, social distancing and mask-wearing directives, and drug/vaccine resource allocation. To evaluate the developed framework, the team will apply it to recent historical epidemics and pandemics, considering COVID-19, H1N1, and Ebola. The research team spans a large multidisciplinary space, including biology, ecology, epidemiology, medicine (infectious diseases, virology and microbiology), computer & information science & engineering, and social sciences (behavioral sciences, health policy, and emerging media).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), Social, Behavioral and Economic Sciences (SBE) and Engineering (ENG).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.