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Sponsored by
  • PIMS
  • MPrime
  • CDM
  • University of Alberta

 

Scientific Program

The scientific program of the summer school consists of a variety of formats.

Short Courses

These are two-lecture (1.5 hour each lecture) tutorials on three main ingredients for mathematical modeling: basic mathematical knowledge on differential equations, basic statistical methods for data analysis, and basic knowledge of epidemiology of infectious diseases. The tutorials also cover three basic type of mathematical models: deterministic models using simple differential equations, stochastic models using Markov processes and stochastic differential equations, and network models using random graphs.
  1. Mathematical basics
  2. Instructor:   Professor Michael Li, University of Alberta

  3. Basic epidemiology for infectious diseases
  4. Instructor:   Drs. Stan Houston and Leah Martin, University of Alberta

  5. Introduction to Deterministic models
  6. Instructor:   Professor Fred Brauer, University of British Columbia>

Advanced Topics

These are 1.5-hour lectures on more advanced models that address important issues related to the disease transmission dynamics such as spatial heterogeneity of the host population, impact of air-travels on the global spread of infectious diseases, effects of time delays in the transmission process, and computation of the basic reproduction number in a variety of mathematical models.

  1. Stochastic models
  2. Instructor:  Professor Julien Arino, University of Manitoba

  3. Network models
  4. Instructor:  Professor Junling Ma, University of Victoria

  5. Compartment models for heterogeneous populations
  6. Lecturer:  Professor James Watmough, University of New Brunswick

  7. Computation of the basic reproduction number
  8. Lecturer:  Professor James Watmough, University of New Brunswick

  9. Meta-population models
  10. Lecturer:  Professor Julien Arino, University of Manitoba

  11. Modeling time delays in disease transmission processes
  12. Lecturer:  Professor P. van den Driessche, University of Victoria

  13. Models for disease transmission in structured host populations.
  14. Lecturer:  Professor Hao Wang, University of Alberta

  15. Parameter estimation and model validation using data.
  16. Instructor:  Professor Junling Ma, University of Victoria

Case Studies

These are 1.5-hour lectures that demonstrate how general mathematical and statistical modeling methodologies are applied to the study of several infectious diseases:
  1. HIV and Resistance to ART
  2. Lecturer:  Professor Michael Li, University of Alberta

  3. Tuberculosis
  4. Lecturer:  Betsy Varughese, University of Alberta

  5. Disease spread through air-travel
  6. Lecturer:  Professor Julien Arino, University of Manitoba

  7. Cholera
  8. Lecturer:  Professor P. van den Driessche, University of Victoria

  9. West-Nile virus
  10. Lecturer:  Professor Huaiping Zhu, York University

Public Lectures

These are lectures given by distinguished scientists and public servants on broader issues related to mathematical modeling and public health.
  1. Contributions of mathematical modeling to controlling infectious diseases Speaker:  Professor Fred Brauer, University of British Columbia

  2. Global control of Tuberculosis
  3. Speaker:  Professor Anne Fanning, University of Alberta

  4. A new method for calculating the basic reproduction number from graph reduction
  5. Speaker:  Professor Mark Lewis, Univeristy of Alberta

  6. Role of mathematical modeling in public health services
  7. Speaker:  Mr. Larry Svenson, Alberta Health

Group Projects

Students and researchers participating in the summer school will be working in groups on assigned research projects. Groups will be formed and assigned a research project at the start of the summer school. Each group will consist of 4-5 participants with a diverse background in training (mathematics, statistics, computer science, epidemiology, and public health). At the end of the summer school, each group will give a presentation of their research project.

Group projects are designed to provide participants with hands-on research experience, and an opportunity for research collaboration in an interdisciplinary environment.