Computational Epidemiology and Public Health Informatics Laboratory

The widescale spread of infectious disease through large areas and populations is an enormously complex phenomenon where good data is hard to get. The Computational Epidemiology lab aims to tackle this problem by using computer-based simulation models and by taking advantage of the proliferation of smart phones and other mobile technology to collect data as it pertains to public health. Through the use of these tools, the lab aims to increase understanding of health policy tradeoffs and improving public health outcomes on a population-wide scale.

Notable Research Accomplishments

Dr. Osgood is a sought after expert in the field of Computational Epidemiology and Public Health Informatics. In addition to carrying out research and teaching university courses, he holds Agent-based modeling bootcamps and workshops for health care professionals in Canada, Australia and the USA. Dr. Osgood has an extensive list of collaborators in Canada and abroad. He has also won numerous awards for excellence in teaching and research.

Current Research Projects

  • Systems models for chronic and infectious diseases
  • Development of scale-modelling techniques for speeding the simulation and analysis of individual-based models
  • Development of formal methods for analyzing the behaviour of individual-based models
  • Large-scale smartphone or mobile wireless sensor network-based data collection
  • Creating tools to better manage and facilitate the dynamic modeling process
  • Exploring the characteristics of and tradeoffs between aggregate and individual-based models
  • Self correcting models
  • Robust models for dynamic decision problems


  • Dr. Nathaniel D. Osgood