Abstract

This session will highlight recent and ongoing work in disease modelling at Statistics Canada. Building on a strong foundation of collecting high-quality population health data, Statistics Canada has developed cancer and chronic disease projection models to aid prevention efforts and policy making. During the COVID-19 pandemic, the appetite to use disease modelling to aid in decision making grew considerably. Disease modelling and modellers were suddenly thrust into the limelight! The pandemic has highlighted that population health modelling, which considers the interplay between sociodemographic factors, risk factors and health/disease states in complex open populations, is perhaps more relevant now than at any other time in history. National Statistical Agencies can play several different roles in developing population health models, including data collection, methodology development, and fostering collaboration with policy departments and external academics. Increasingly, these multidisciplinary and multi-institute teams work within a modern “data-science” and Open Science framework to support complex modelling projects. Presenting this work at the ISI World Statistics Congress will allow Statistics Canada researchers to gain a diverse and rich perspective on their work from the international statistics community.