Schedule: 14:30-16:30 on August 9
Location: Room 202, Jeffery Hall (48 University Avenue)
Biomath modeling is a discipline that requires the creative use of mathematical tools to solve problems in biology. Historically, differential equations have been a very useful tool for modeling problems from biology, for example the Lotka Volterra predator-prey model gives some insight into ecological interactions, and the Kermack McKendrick SIR model provides an explanation for some results in epidemiology. The ultimate goal is to create models that deepen our understanding of biological phenomena. In this seminar we will take a hands on approach on creating models to investigate problems in epidemiology by modifying the SIR model to fit specific scenarios. Some modifications we will discuss include using Markov chains to model small populations, using partial differential equations or networks to model spatially distributed populations, and using game theory to incorporate human behaviour into models.
Assumed Knowledge:
- Some knowledge of differential equations
- Some programming experience (such as R, Python, or Matlab)
- Some knowledge of epidemiology, ecology and evolution
Participants are encouraged to bring their personal laptops and to have the latest version of Python 3 installed. It may also be helpful to read this Python tutorial ahead of time.
Please do not hesitate to contact Tyler Meadows if you have any questions.