SCC-IRG JST: PanCommunity: Leveraging Data and Models for Understanding and Improving Community Response in Pandemics

The goal of this integrative research effort is to enhance the understanding of the complex relationships characterizing pandemics and interventions under crisis. The global-scale response to the COVID-19 pandemic triggered drastic measures including economic shutdowns, travel bans, stay-home orders, and even complete lockdowns of entire cities, regions, and countries. The need to effectively produce and deliver PPE, testing and vaccines has affected different communities of stakeholders in different ways, requiring coordination at family/business units, counties/states to federal level entities. This project, therefore, considers communities at local, federal, and international (US and Japan) scales and investigate impact of testing, preventative measures and vaccines, when used in combination, to improve community and inter-agency response at the different scales. The impacts of this research includes technologies to help save lives, restore basic services and community functionality, and establish a platform that supports core capabilities including planning, public information, and warning. The project organizes an interdisciplinary community, bringing together (a) computer/data scientists, (b) domain and social scientists and policy experts, (c) federal, state, local governments, (d) industry and nonprofits, and (e) educators, to serve as a nexus for major research collaborations that will: overcome key research barriers and explore and catalyze new paradigms and practices in cross-community response to pandemics; enable development and sharing of sustainable and reusable technologies, coupled with extensive broader dissemination activities; act as a resource for public policy guidance on relevant strategies and regulations; and provide education, broadening participation, and workforce development at all levels (K12 to postgraduate) for the next generation of scientists, engineers, and practitioners. The project involves a close collaboration between Arizona State University in the United States, and Kyoto University in Japan. The project involves interfaces with community partners in Tempe, Arizona and Kyoto, as well as national-level civic organizations in both the U.S. and Japan.

This effort aims to answer several fundamental research challenges across computing and community health: (a) epidemic, testing, vaccination and behavior model/data integration and alignment, (b) multi-model and multi-scale simulation ensemble creation and decision support, and (c) multi-scale social impact of decision making across communities. To tackle these challenges, the project develops new data and model informed methods, brought together in PanCommunity, to develop testing and vaccination policies, considering coordination, collaboration, and competition across communities at multiple scales. This project will develop a novel model description, assessment, and composition framework that supports seamless integration of independently developed, reusable scientific model and analysis components within the same framework as the data for understanding and improving community response in pandemics. This project also develops novel coupled simulation and optimization frameworks that account not only for economical but also social costs in supporting decision making.

This project is a joint collaboration between the National Science Foundation and the Japan Science and Technology Agency.

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.