In the past year, the ongoing COVID-19 pandemic has severely disrupted the livelihoods of our planet’s human inhabitants, infecting over 85 million individuals, and causing nearly 2 million deaths. What actions might have been taken to minimize the severity of this pandemic (and others before it in the past decades such as Zika, SARS and Ebola)? In retrospect, many actions could have played key roles: environmental monitoring for potential animal-to-human infection spillovers, establishment of pipelines for rapid vaccine development and optimal deployment and distribution, designing data-science tools to accurately forecast trajectories, fast and adaptive syndromic surveillance and behavior tracking, designing and timing effective interventions, training susceptible individuals for measures needed to inhibit the spread of infectious agents, and others. What lessons have been learned and what gaps in our knowledge, methodologies, technologies, and policies remain? The investigators propose a two-day multi-disciplinary National Symposium on PRedicting Emergence of Virulent Entities by Novel Technologies (PREVENT) to begin to address these and related challenges. As a whole the highly interdisciplinary organizing team has significant experience in various aspects of the topics touched upon by this symposium. Bridging fundamental gaps in what is known (and perhaps even what is knowable) can require coordination that goes far beyond sharing of instruments, standardization, or the exchange of methods and data; these define broader societal challenges of complex problems beyond pandemic prediction. This meeting will help enable coordinated team-science efforts that can assist in bringing disparate groups together, whether in small teams or large teams, including bringing in the public as citizen scientists.

Key in fostering convergence for predictive intelligence for pandemic prevention will be co-envisioning computing, science and engineering in ways that are integrated across disciplines so that community efforts are optimally suited to (and nimbly able to) respond to and prevent new pandemics. The symposium has been structured around four themes and perspectives: Molecular, Physiological, Population/Epidemiological and End-end/Multi-scale. The proposed meeting will provide a valuable opportunity for the community to begin to build the necessary convergence. A combination of plenary talks, short talks, panel discussions and small breakout thought sessions will be used to help achieve these aims. For several significant reasons, predictive intelligence for pandemic prevention stands to benefit by drawing upon convergent computation, science and engineering insights alongside traditional disciplinary repositories of expertise.

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.

Project Start
Project End
Budget Start
2021-02-01
Budget End
2021-09-30
Support Year
Fiscal Year
2021
Total Cost
$11,378
Indirect Cost
Name
Regents of the University of Michigan - Ann Arbor
Department
Type
DUNS #
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109