PIPP Phase I: BEHIVE - BEHavioral Interaction and Viral Evolution for Pandemic Prevention and Prediction

The COVID-19 pandemic has highlighted human vulnerability to infectious disease outbreaks and reinforced the need for improved data-driven response and preparedness. The BEHIVE (BEHavioral Interaction and Viral Evolution) research team for Predictive Intelligence for Pandemic Prevention (PIPP) aims to tackle a fundamental challenge in disease outbreak prevention by integrating the study of human behavior using a computational data-driven lens. The impact of human behavior and social interactions remain underutilized in efforts spanning scenario development, forecasting, and epidemic mitigation. Proposed educational and outreach activities will train early career researchers and practitioners in PIPP. The trans-disciplinary nature of the project including connections with the humanities will encourage diverse cohorts of researchers to engage in this public-facing field. Several accelerating trends, such as widening data collection, new Artificial Intelligence (AI) and Machine Learning (ML) techniques, high fidelity computational modeling and recent surge in social/behavioral knowledge due to COVID-19, create an opportunity to tackle the challenge of integrating human behavior into epidemic response using a synergistic team-science approach. Project will develop methods incorporating behavioral feedback to bridge mechanistic and AI models, to provide specificity and context needed via genomic surveillance and robust predictions, and to empower coordinated decision making by building strategic portfolios. These efforts will lead to novel AI/ML frameworks, new modeling/decision-making paradigms, facilitate early warning systems and inform mitigation efforts to prevent pandemics and reduce risk of outbreaks in the first place. The diverse interdisciplinary team consists of computer scientists, biologists, engineers, and behavioral scientists, along with experts in medicine and public health (from Georgia Tech, MIT, Michigan, UGA and Mayo Clinic) with broad and significant expertise in epidemic research spanning foundational research and intervention-focused work during the COVID-19 pandemic. The project team will also partner with multiple academic, industrial, government public health and non-profit setups, which will help enlarge the impact of the proposed research. 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.