Chronic disease and multimorbidity are reshaping the demands on health systems. As populations age, risk factors evolve, and health inequities widen, planning for the future requires rigorous, data-driven projections grounded in population health methods. Our burden of illness research program produces long-range projections of chronic disease and multimorbidity to inform health system planning, policy development, and prevention strategy. By integrating decades of population-wide health administrative data with demographic projections and disease modelling, we generate actionable evidence on how illness will unfold across populations, regions, and communities in the coming decades.
Health systems are under growing pressure from rising chronic disease, increasing multimorbidity, and an aging population. Yet most planning still relies on short-term utilization trends rather than forward-looking models that account for the complex interplay of demographics, disease trajectories, social determinants, and risk factors. Without these projections, investments in infrastructure, workforce, prevention, and community care risk being too little, too late, or poorly targeted. We combine comprehensive, linked health data with validated chronic disease algorithms, demographic forecasts, and a newly developed multimorbidity scoring framework. This approach allows us to project not just the volume of illness, but its severity and complexity, and to understand how the burden is distributed across population groups. That study projected that the number of people living with major illness would nearly double between 2020 and 2040, with significant implications for system capacity, equity, and the model of care. We are now expanding this work across several dimensions.
Our research program is actively growing in scope and depth. We are also developing regional and sub-provincial projections to provide locally relevant evidence for health system planning. We are integrating sociodemographic and structural risk factors into how we present these estimates. This allows us to produce equity-stratified estimates that reveal how the burden of illness is distributed across population subgroups and where disparities are expected to widen. A distinct stream of work focuses on children and youth, whose chronic disease patterns differ markedly from those of the adult population. Finally, we are adapting our framework for application in other provinces and jurisdictions. While the foundational methodology was developed using Ontario’s data infrastructure, the approach is designed to be portable, enabling comparable projections wherever linked population health data are available. This cross-jurisdictional work supports collaborative learning and comparative health system planning.
Burden of illness projections provide the evidence base for some of the most consequential decisions in health policy, from where to build new infrastructure, to how to build capacity in community care and prevention, strengthen population health and identify which communities need the most support. Our work is designed to serve policymakers, health system leaders, and researchers who are grappling with these questions and need robust, transparent, population-level estimates to guide their decisions. By making the future burden of illness visible and concrete, we aim to shift the conversation from reactive crisis management toward proactive, equitable, and sustainable health system planning.
Outputs
Rosella LC, Buajitti E, Daniel I, Alexander M, Brown A. Projected patterns of illness in Ontario. Toronto, ON: Dalla Lana School of Public Health; 2024. Link
OHA Website for Projected Patterns of Illness in Ontario: Ontario Hospital Association Projected Patterns of Illness in Ontario
Buajitti E. and Rosella LC. Validation of a health system-focused morbidity score for the Canadian population. Society for Epidemiologic Research Annual Meeting; 2025 Jun 10–13; Boston, MA. Link
Projected Patterns of Illness Report: Regional Analysis Regional Analysis Overview