The lead institution is the Fred Hutchinson Cancer Research Center (FHCRC) in Seattle, led by Elizabeth Halloran.
The overall objective of this multi-institutional MIDAS Center of Excellence is to provide national and international leadership in computational, statistical, and mathematical research, education and outreach, and public health policy related to infectious diseases and interventions.
Centerwide programs include:
- Training, Outreach, and Diversity plans
- Annual Workshops
- Annual Symposia
- Visitors Program
- Seminar Speakers Program
Modeling, Spatial, Statistics
Lead: Prof. Ira Longini, University of Florida
Objective: to develop, validate, and implement mathematical and statistical models for the transmission of naturally occurring infectious diseases and bioterrorism agents.
Lead: Prof. Pejman Rohani, University of Georgia
Objective: development of cutting-edge statistical inference methods and their application to high-dimensional disease incidence data.
Understanding Transmission with Integrated Genetic and Epidemiologic Inference
Co-Leads: Dr. Eben Kenah, University of Florida; Dr. Trevor Bedford, FHCRC
Objective: to develop, implement and validate novel methods to perform joint inference using combined epidemiologic and genetic data.
Dynamics and Evolution of Influenza Strain Variation
Lead: Prof. Rustom Antia, Emory
Objective: to understand how diseases of public health relevance exhibit continual evolution by generating new strains which change key regions (epitopes) recognized by the immune system, allowing these new strains to infect some of the individuals with immunity to previous strains.
Lead: Prof. James Koopman, University of Michigan
Objective: to improve communication and understanding between key modelers so they can work more effectively together.
Software Development and Core Facilities
Lead: Prof. Alessandro Vespignani, Northeastern University
Objective: to develop a multi-scale Modeling Computational Platform (MCP) for Infectious disease simulations; to develop new features and GUIs for statistical tools developed by our research groups.