In this episode, we spoke with Dr Jane Heffernan from York University about using mathematical modelling methods for understanding and controlling infectious diseases in individuals (or immunology) and in populations (or epidemiology), and discuss the differences between within-host and population-level modelling.
This webinar will address two analyses of routine surveillance data designed to support parameterisation and construction of mechanistic mathematical models of AMR.
In this episode, we spoke with Dr Melanie Cousins from the Public Health Agency of Canada about some of her PhD work, which was recently published in an article titled “Is scientific evidence enough? Using expert opinion to fill gaps in data in antimicrobial resistance research”.
This episode will provide an overview of the National Advisory Committee on Immunization (NACI) health economics guidelines for the evaluation of vaccination programs in Canada, and how they can be used to inform best practices and promote standardized and high-quality evidence for public health decision making.
Mathematical modelling is a research method that can improve public health planning and infectious disease control. Big Data refers to very large and diverse datasets that are analyzed at high velocity to reveal patterns, trends, and associations. NCCID supports an expanding area of knowledge translation and exchange related to mathematical modelling and the use of…
In this episode, Dr. Michael Li spoke with us about the past, present, and future of infectious disease modelling, the different roles and responsibilities of a math modeller, and how he envisions math modelling for public health in the future.