Establishing the Scientific Foundation for Quantitative Public Health Decision Making

[ Français ]
April 29 - May 1, 2013
Fields Institute
David L. Buckeridge (McGill), Charmaine Dean (Western), Jianhong Wu (York)

Public health authorities must decide how to best use limited resources to prevent and control disease and to promote health. Decisions should be made by bringing current knowledge to bear on available data. In current public health practice, this decision making process usually occurs in an ad hoc manner, with the aid of neither quantitative models of diseases and interventions nor timely and accurate data. Advances in surveillance, disease modeling, and simulation, however have the potential to modernize public health decision-making by allowing data to be acquired rapidly and incorporated into disease models to support exploration of decisions through simulation. Such a quantitative framework for decision-making has the potential to greatly enhance the effectiveness of disease prevention and control activities and thereby advance population health. Development of the scientific foundation for quantitative decision-making in public health requires: i) Methods for using multiple surveillance data streams to estimate critical parameters needed to simulate human behavior and disease; and ii) Methods of simulation modeling that will enable assessment of the likely outcomes of interventions in complex real-world settings.

We expect the workshop will pull together leading research groups and encourage open exchange of ideas and results. Given the increasing amount of research in this area, and the breadth of journals in the scientific and biomedical literature publishing results of this work, the workshop will be critical for sharing ideas to advance research activities and understand how research results can be translated in practice. We are also interested in encouraging through the workshop the creation of topical publications in the form of journal special editions or monographs. The workshop will also help participants to identify opportunities for moving promising methods into public health practice settings where they can be evaluated in terms of usability and their effect upon outcomes.

This three-day workshop will offer (a) Half-day tutorials (b) Invited lectures from surveillance, data analysis and modeling; (c) panel and group discussions.