Improving Predictive Intelligence for Pandemic Prevention
The COVID–19 pandemic has shown how epidemiologic modeling can inform decision making in times of crisis and uncertainty. It has also highlighted significant gaps that must be addressed to create ongoing, interdisciplinary collaborations that can provide more effective predictive intelligence for pandemic prevention (PIPP). The Robust Epidemic Surveillance and Modeling (RESUME) team has experience supporting public health stakeholders during the COVID–19 pandemic and drawing on that has identified critical gaps in three broad areas.
- Communication and collaboration among researchers and public health stakeholders
- Integration of diverse data streams including surveillance data
- Foundational work to predict future pathogens and their evolution
Addressing These Gaps
Through funding from the National Science Foundation (Grant No. 2200234) the project brings together an interdisciplinary team with expertise in epidemiologic modeling, public health, policy and risk analysis, social sciences, decision modeling, artificial intelligence (AI), high-performance computing (HPC), molecular engineering, structural biology, and large-scale data management and assimilation. The investigators engage modelers and public health stakeholders to broaden participation in collaborative modeling, carry out pilot projects, and develop training modules for generalizable approaches to collaborative pandemic intelligence.
How It Works
The project convenes workshops with stakeholders and researchers and carries out pilot studies to refine our vision for an interdisciplinary Robust Epidemic Surveillance and Modeling (RESUME) center, that advances the science and practice of pandemic prediction and prevention across three thrusts.
OSPREY: Open Science Platform for Robust Epidemic analYsis
To support these thrusts, the project demonstrates a sustainable simulation, data, decision support, and learning collaborative platform, the Open Science Platform for Robust Epidemic analYsis (OSPREY). The OSPREY platform serves as crucial PIPP cyberinfrastructure built to leverage investments in forthcoming exascale and increasingly ubiquitous HPC and data resources. In particular, OSPREY focuses on the following objectives:
- Data ingestion, curation, and management: OSPREY enables automated, continuously running data assimilation analyses for melding data streams with up-to-date model forecasts
- HPC workflows for decision making: OSPREY facilitates access to HPC resources for decision-relevant time-to-solution analyses
- Shared development environment (SDE) for rapid collaboration: OSPREY enables flexible and scalable approaches to support exploration, experimentation, verification, validation, and collaboration as public health crises evolve.
