RAPID: Modeling and Analytics for COVID-19 Outbreak Response in India: A multi-institutional, US-India joint collaborative effort

该项目包括研究与大流行科学有关的三个广泛问题，特别关注正在印度爆发的COVID-19疫情。来自弗吉尼亚大学、普林斯顿大学、疾病动力学、经济与政策中心、印度科学研究所和班加罗尔印度统计研究所的团队成员将研究三个核心问题：(i)生物监测，（ii）预测和（iii）疫苗分配。任务的选择是基于当前的需求，问题的重要性，以及它们能够及时解决的可能性。第一个主题是综合主动生物监测。在这次大流行期间，病毒突变、人类行为、疫苗和公共政策之间的相互作用是前所未有的。管理这种大流行的一个组成部分是生物监测；这包括收集样本，跨空间和时间对病毒进行测试和测序，并将这些信息结合起来评估病毒株的分布和影响。该项目将使用智能生物监测的诱导性框架——预算有限的测试、基因组测序和识别新变异及其传播和进化的方法。第二个主题是预测地区/州一级的COVID-19动态。预测COVID-19动态在各地都具有挑战性；在印度，由于一些原因，包括嘈杂的数据，死者的漏报，缺乏关于执行的国家行动计划的遵守情况的信息等，这更具挑战性。该项目将利用团队成员在这一主题上正在进行的工作，为印度开发创新的COVID-19预测方法。它将探索使用多个数据源来对抗不一致性，并结合其他建模团队公开可用的预测，以获得强大的综合预测。第三个主题是疫苗的优先排序、分配和分发。该项目将开发模型和分析工具，以研究与疫苗的优先次序、分配和分发有关的一系列问题。由于免疫力下降和/或第一波传播有限，2021年初第二次大幅增加突显了广泛的易感性。由于不受控制的传播可能导致新的变异，以及疫苗开发出现的新可能性，在印度和其他地方，快速、有效和公平的疫苗运动仍然是控制COVID-19的最重要途径。该项目将带来新的方法，将多尺度模拟与人工智能和机器学习的最新技术相结合，以获得上述问题的可实施解决方案。这些方法也将是可推广的——目标是发展应对未来流行病所需的技术能力。美国和印度学术机构之间的这种创新伙伴关系将为未来在这一具有全球重要性的重要主题领域开展联合合作奠定基础。该奖项反映了美国国家科学基金会的法定使命，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。

This project includes study of three broad problems pertaining to pandemic science with a specific focus on the ongoing COVID-19 outbreak in India. Team members from U. Virginia, Princeton University, Center for Disease Dynamics, Economics & Policy, the Indian Institute of Science and the Indian Statistical Institute, Bengaluru will study three central problems: (i) biosurveillance, (ii) forecasting and (iii) vaccine allocation. The choice of tasks is based on current needs, the importance of the problem, and the likelihood that they can be solved in a timely fashion. The first topic is integrated active biosurveillance. During this pandemic the interplay between viral mutations, human behavior, vaccines, and public policies has been unprecedented. An integral element of managing such a pandemic is biosurveillance; this involves collecting samples, testing and sequencing viruses across space and time, and combining this information to assess the distribution and impact of the viral strains. This project will use an abductive framework for smart biosurveillance – budget constrained methods for testing, genomic sequencing and identifying new variants and their transmissibility and evolution.The second topic is forecasting COVID-19 dynamics at the district/state level. Forecasting COVID-19 dynamics has been challenging everywhere; in India it has been even more challenging for a number of reasons including noisy data, undercounting of the deceased, lack of information on compliance of NPIs implemented, etc. This project will leverage ongoing work by team members on this topic to develop innovative COVID-19 forecasting methods for the Indian context. It will explore the use of multiple data sources to combat the inconsistencies and incorporate publicly available forecasts from other modeling teams to obtain robust ensembled forecasts.The third topic is vaccine prioritization, allocation, and distribution. This project will develop models and analytical tools to study a range of questions related to vaccine prioritization, allocation and distribution. The significant second surge has highlighted widespread susceptibility in early 2021, due either to waning immunity and/or limited spread of the first wave. With the possibility of novel variants due to uncontrolled spread, and emerging possibilities in vaccine development, an expedited, effective, and equitable vaccine campaign remains the most important pathway to controlling COVID-19 in India and elsewhere. The project will lead to new methods that combine multi-scale simulations with recent techniques in AI and machine learning to obtain implementable solutions to the problems above. The methods will also be generalizable -- the goal is to develop the needed technical capability to respond to future pandemics. This innovative partnership between academic institutions in the US and India will form the basis of future joint collaborations on this important topical area of global importance.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.