CDC Grant — Submitted
Principal Investigator: Dr. David Ussery, Oklahoma State University
Co-Investigators: Dr. Lucas Stolerman & Dr. Arghavan Alisoltanidehkordi, OSU
Project Summary
Overview, Need, and Purpose: Rural regions face sparse, delayed, and fragmented surveillance for seasonal and zoonotic influenza. Oklahoma reported only 112 influenza isolates in early 2026 despite the intersection of human seasonal influenza, swine production, avian migration, dairy-cattle H5N1 concern, and rural health systems underscoring the need for integrated human, animal, environmental, and genomic surveillance systems. The purpose of this project is to establish an Oklahoma State University influenza modeling and forecasting site that improves real-time forecasting, control planning, and public health communication.
Approach and Activities: We will establish a multidisciplinary network site led by expertise in viral genomics, mathematical epidemiology, machine learning, and veterinary/public-health surveillance. The core operational product will be monthly real-time probabilistic forecasts submitted to FluSight during the influenza season. Clinical and surveillance targets will include influenza hospital admissions and emergency department influenza percentages when available. Subtype-aware features will be generated for influenza A/H3N2, A/H1N1pdm09, B/Victoria, and H5-relevant signals, with careful separation between surveillance indicators and true incidence. We will mine large-scale influenza genome resources (e.g., GISAID with ~800,000 viruses and GenBank 1.8 M records) to characterize viral diversity and emerging variant signals. Genomic and protein language-model embeddings will be combined with structural annotations to produce interpretable covariates, such as clade-growth indicators. These covariates will be incorporated into forecasts and mechanistic models.
We will develop and evaluate an 8-target colorimetric spot-assay concept for core seasonal influenza and spillover-relevant targets. This component will be treated as a low-cost rural surveillance pilot, not as a replacement for validated laboratory testing. Assay outputs will be evaluated as potential covariates, sequencing triggers, or local presence/absence indicators.
Outcomes, Impact, and Collaboration: Oklahoma State University (OSU) will advance CDC priorities by delivering a scalable, One Health influenza forecasting system that strengthens rural situational awareness and decision support. OSU will also develop zoonotic spillover models leveraging agricultural and veterinary surveillance, enabling a multi-modal forecasting network that enhances CDC insight in rural and agricultural regions. The anticipated impacts include reduced morbidity and mortality through optimized prevention strategies, and strengthened readiness for pandemic and emerging respiratory threats across the South-Central U.S. region. OSU will collaborate across the CDC forecasting network, and leverage existing computational infrastructure and collaborations with the Oklahoma Animal Disease Diagnostic Laboratory, the Oklahoma Center for Respiratory and Infectious Diseases Oklahoma State Department of Health, tribal health systems, rural healthcare providers and national partners to serve as a high-impact node within the CDC’s network to deliver scalable, transparent, actionable modeling.