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Canadian Journal of Infectious Diseases and Medical Microbiology
Volume 26, Issue 4, Pages 191-195
Special Article

Improving Public Health Policy through Infection Transmission Modelling: Guidelines for Creating a Community of Practice

Seyed M Moghadas,1 Margaret Haworth-Brockman,2 Harpa Isfeld-Kiely,2 and Joel Kettner2

1Agent-Based Modelling Laboratory, York University, Toronto, Ontario, Canada
2National Collaborating Centre for Infectious Diseases, Winnipeg, Manitoba, Canada

Copyright © 2015 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


BACKGROUND: Despite significant research efforts in Canada, real application of modelling in public health decision making and practice has not yet met its full potential. There is still room to better address the diversity of the Canadian population and ensure that research outcomes are translated for use within their relevant contexts.

OBJECTIVES: To strengthen connections to public health practice and to broaden its scope, the Pandemic Influenza Outbreak Research Modelling team partnered with the National Collaborating Centre for Infectious Diseases to hold a national workshop. Its objectives were to: understand areas where modelling terms, methods and results are unclear; share information on how modelling can best be used in informing policy and improving practice, particularly regarding the ways to integrate a focus on health equity considerations; and sustain and advance collaborative work in the development and application of modelling in public health.

METHOD: The Use of Mathematical Modelling in Public Health Decision Making for Infectious Diseases workshop brought together research modellers, public health professionals, policymakers and other experts from across the country. Invited presentations set the context for topical discussions in three sessions. A final session generated reflections and recommendations for new opportunities and tasks.

CONCLUSIONS: Gaps in content and research include the lack of standard frameworks and a glossary for infectious disease modelling. Consistency in terminology, clear articulation of model parameters and assumptions, and sustained collaboration will help to bridge the divide between research and practice.