PIPP Phase I: Comprehensive, Integrated, Intelligent System for Early and Accurate Pandemic Prediction, Prevention, and Preparation at Personal and Population Levels

The COVID-19 pandemic demonstrates that our country desperately needs a next generation public health system that can quickly adapt to, and learn from an expected or not-expected public health crisis. By taking advantage of recent advances in artificial intelligence (AI), such a system shall be able to predict, detect, and respond to rapidly evolving emergent public health crises, and resume its prior performance level rapidly in a sustainable and scalable way. Towards that goal, this project aims to tackle the grand challenge of sociotechnical design of nation-wide digital infrastructure for pandemic prediction and prevention, which is built on the foundation of privacy and inclusiveness. A multi-disciplinary team of researchers from multiple institutions will lead a broad range of fundamental and integrated research projects that incorporate both micro-level granular data and population-level data to tackle the grand challenge from different aspects. A set of activities, including meetings, workshops, and seminars, have been carefully planned to create an effective research team, to engage diverse and inclusive stakeholders (e.g., public health departments, health care/hospital systems, industrial/private sectors, and geographically and ethnically diverse community stakeholders), and to educate and train next generation researchers to conduct team science. In order to develop a digital, autonomous, and distributed infrastructure that is also privacy preserving, the team will focus on the architecture for data storage and collection, as well as privacy enablers for data sharing. The data collection infrastructure and privacy enabler technologies will (i) carefully balance data utility and privacy; (ii) balance vulnerability for known privacy risks and institutional needs to protect sensitive data; and (iii) allow individuals (data donors) to have full control over their data and to give informed consent while sharing their data in different ways with different data collectors (researchers). In addition, the team will develop a set of highly integrated research projects that work coordinately and intelligently for pandemic prevention that also broaden participation and inclusion. The projects include (i) early detection using wearable devices in combination with population level social, economic, cultural and environmental indicators; (ii) mathematical modeling of pathogen transmission, hotspot prediction based on spatio-temporal analysis, and mitigation; (iii) multi-level and multi-faceted surveillance; and (iv) technological preparation for new diseases based on drug repositioning. The two aims are complementary to each other and work synergistically to achieve the ultimate goal of early and accurate pandemic prediction, prevention, and preparation at personal and population levels that will also ensure privacy and inclusion. 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.