Funding is sought for the Summer Institute in Statistics and Modeling in Infectious Diseases (SISMID) at the University of Washington. This proposal specifically requests funds for student / postdoctoral fellow participant registration scholarships and travel and instructor stipends. The SISMID has been held each summer since 2009. This proposal requests funds for 2014-2018. The summer program provides workshops on statistical methods and dynamic modeling in infectious diseases, causal inference, inference on networks, evolutionary phylodynamics, metagenomics, and evaluating interventions, particularly vaccination. The SISMID also provides an introductory workshop on immunology and modeling of the immune system. Participants are drawn from academia, industry and government. The 30 instructors are drawn from the University of Washington, Fred Hutchinson Cancer Research Center (FHCRC), other academic institutions in the USA and other countries, and industry. The SISMID is directed by M. Elizabeth Halloran, Professor in the Department of Biostatistics at the University of Washington and FHCRC. The 2014 SISMID proposes to offer the following 15 2.5-day modules: 1. Probability and Statistical Inference; 2. Introduction to R; 3 Mathematical Models of Infectious Diseases; 4. Causal Inference; 5. Stochastic Epidemic Models with Inference; 6. Infectious Diseases, Immunology, Within Host Models; 7. MCMC I; 8. Design and Analysis of Vaccine Clinical Trials; 9. Network Theory in Infectious Diseases; 10. MCMC II for Infectious Diseases; 11. Stochastic Dynamic Simulation Models; 12. Evolutionary Dynamics and Molecular Epidemiology of Viruses; 13. Spatial Statistics; 14. Metagenomic Data Analysis; 15. Evaluating Immune Correlates of Protection. This award will support 80 student / postdoctoral fellow participants.
Statistical and mathematical methods for the study of infectious diseases and for discovery and evaluation of interventions have become increasingly important. The Summer Institute in Statistics and Modeling in Infectious Diseases provides training in statistical and mathematical modeling to infectious disease researchers, statisticians, computational biologists and other scientists. The research education allows them to design studies, analyze data, and model dynamics and evolution of infectious diseases relevant to important public health and basic science questions.