Expeditions: Global Pervasive Computational Epidemiology

This Expeditions project will enable novel implementations of global infectious disease computational epidemiology by advancing computational foundations, engineering principles, theoretical understanding, and novel technologies. The innovative tools developed will provide new analytical capabilities to decision makers and result in improved science-based decision making for epidemic planning and response.

Novel computational technologies and tools are being developed as a part of the Expeditions project and will be used for epidemic planning and response. These tools will facilitate enhanced inter-agency and inter-government coordination and outbreak response. The team is working closely with many local, regional, national, and international public health agencies and universities to apply and deploy powerful technologies during epidemic outbreaks, including the ongoing COVID-19 pandemic and other epidemics that will occur during the course of the project.

International scientific networks linked to a comprehensive postdoctoral and graduate student training program are being established. Educational programs to foster interest in and increase understanding of computational science in addressing the complex societal challenges due to pandemics will also be developed. The team, with partners in Asia, Africa, Europe, and Latin America, is working to produce multidisciplinary scientists with diverse skills related to public health.

The novel implementations of this project are enabled by the development of a rigorous computational theory of spreading and control processes on dynamic multi-scale, multi-layer (MSML) networks, along with tools from AI, machine learning, and social sciences. New techniques resulting from this research will make it possible to develop and apply large-scale simulations of epidemics and social interactions over MSML networks. These simulations, in turn, provide fundamentally new insights into how to control epidemics. Pervasive computing technologies are being developed to support disease surveillance and real-time response.

These computational advances are also generalizable; that is, they are applicable to other areas such as cybersecurity, ecology and social sciences. The Expeditions project takes into account emerging concerns and constraints that include: preserving privacy of individuals and vulnerable groups, enabling model predictions to be interpreted and explained, developing effective interventions under uncertain and unknown network data, understanding strategic and adversarial behaviors of individual agents, and ensuring fairness of the process across the entire population.

The research team includes experts from multiple disciplines and will address these societal concerns and constraints in practical, impactful, and novel ways, including the development of computational tools and techniques to support sound, ethical science-based policy pertaining to public health infectious disease epidemiology. The Center for Computational Research in Epidemiology (CoRE) at the University of Virginia will be established as a part of the project. CoRE will develop transformative ways to support real-time epidemiology and facilitate improved outbreak response to benefit the society.

Expeditions Data Types and Sources

The Expeditions team includes collaborators from the Center for Disease Dynamics, Economics & Policy (CDDEP), Georgia Tech, Indiana University, Jackson State University, Lawrence Livermore National Laboratory (LLNL), Massachusetts Institute of Technology, North Carolina A&T State University, Oak Ridge National Laboratory (ORNL), Princeton University, Stanford University, University of Maryland, University of Virginia, Virginia Tech, and Yale University.

UVA COVID-19 model predicts coronavirus cases in Virginia could peak by Thanksgiving [WRIC Richmond; October 21, 2020]

How prepared are we for the next pandemic? [ET Healthworld; April 29, 2020]

Consortium led by University of Virginia Biocomplexity Institute funded by $10 million, five-year US National Science Foundation grant [Express Healthcare; April 27, 2020]