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

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.