The Portal brings together a broad selection of resources from all six of the National Collaborating Centres (NCCs). Search for resources by clicking on NCC, Type, Topic and Core Competency.
Please note: the Portal is not exhaustive and not all resources are indexed by PHAC Core Competency.
Behind the Curtain of Mathematical Modelling : Inside a collaborative modelling project on public health strategies for syphilis management
This case study describes the experiences of an interdisciplinary team associated with the Winnipeg Regional Health Authority (WRHA), the University of Toronto, and Harvard University who came together to apply mathematical modelling to assess the impact of a newly designed intervention to reduce the burden of syphilis in Winnipeg, Manitoba. Their story illustrates how mathematical modelling can provide timely evidence to guide decision-making by public health planners and practitioners throughout the implementation of a new intervention. The lessons they share may help to demystify modelling and reveal the benefits of collaborations between modellers and public health personnel.Read More
This document provides a review of terms commonly used in modelling studies of influenza infection spread and control. The objective is to understand the similarities and discrepancies between definitions of the same terms used in different studies. Standardization of terms should reduce variation in study results produced by different research communities, and should improve the accessibility and policy-relevance of new knowledge for public health decision-makers.Read More
This document provides details of the proposed logical framework for influenza infection, including several modules for public health interventions and their effects in prevention and control of illness. These interventions include vaccination, use of antiviral drugs, and hospitalization. The aim of this logical framework is to enhance the utility and uptake of modelling for public health responses by building a conceptual framework for common assumptions, plausible interventions, disease outcomes, and the impact of control measures at various stages of infection.Read More