Understanding and Assessing Quantitative Modelling Research

This document provides an overview of how to critically assess a research article which uses quantitative, data-driven mathematical modelling to examine infectious disease transmission. Included is a Quick Reference Guide which aligns with the process of quantitative model development and the format of research articles and is meant to assist in a critical review of the research.

Mathematical Modelling in Public Health Planning: Flu Vaccine

In public health, mathematical modelling helps us answer difficult, real-world questions and understand complex relationships between biological, demographic, and environmental factors. Modelling helps answer infectious disease-related questions like “What is the best vaccine to protect an elderly population at increased risk of infection from seasonal influenza?” Modellers interpret the model outcomes and draw conclusions to…

Mathematical Modelling in Public Health: Tuberculosis

In public health, mathematical modelling helps us answer difficult, real-world questions and understand complex relationships between biological, demographic, and environmental factors. Modelling helps answer infectious disease-related questions like “What are the potential effects of three different interventions on a specific disease?” Modellers interpret the model outcomes and draw conclusions to make accurate, evidence-driven and transparent…

Behind the Curtain of Mathematical Modelling : Inside a collaborative modelling project on public health strategies for syphilis management

Case study on the application of mathematical modelling to assess the impact of a newly-designed intervention on 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.