Epidemiology & Biostatistics : Mathematical models of infectious diseases –computer simulations of epidemics–enable detailed analyses and understanding of factors affecting the distribution of infections/diseases in populations and now play a key role in policy making. Covered topics include: short-term dynamics of infections (R0), compartmental models, stochastic models (including agent-based), contact patterns and heterogeneity, and Bayesian model calibration. The learning objectives are: 1) recognize research questions that can be addressed using modeling; 2) develop, parameterize, calibrate, and analyze simple infectious disease models in R; and 3) critically appraise scientific modeling papers.
Terms: Winter 2023
Instructors: Maheu-Giroux, Mathieu (Winter)
Prerequisite(s): EPIB 621 or permission of the instructor
Restrictions: Not open to students who have taken EPIB 676 when topic was "Mathematical Models of Infectious Diseases".
This is an intermediate-level quantitative course. Previous courses in calculus and biostatistics are recommended (in doubt, contact the instructor prior to registration). A working knowledge of the R statistical software (or equivalent) is mandatory (data structures, function, loop, etc.).