Welcome to our first Personal Support Worker (PSW) modelling and scenario-testing prototype—a tool we will continue to evolve to better support health workforce modellers, health system leaders, and education planners anticipate the supply of PSWs needed to care for Canadians. This model allows users to test the relative impact of alternative population growth scenarios on future PSW supply, by jurisdiction and by care setting, up to 2048.

This agent-based microsimulation model leverages data from Statistics Canada’s Labour Force Survey and population projection estimates. Agent-based microsimulation modelling is a computational approach that uses real-world aggregated data to create a simulation of individual agents—such as health workers—and how they behave and interact with each other. This model can be used to test different population scenarios and predict what the future workforce might look like.

Our PSW prototype is in its testing phase. We are soliciting your input to help us refine the model to ensure the best performance, legitimacy, accuracy, and reproducibility. To prioritize future refinement of the model, we are particularly interested in hearing about use cases that describe how this tool could support real-world decision-making. Our goal is to launch a more advanced and robust version of the PSW microsimulation model in the fall/winter of 2025. 

The projection methodology for this agent-based microsimulation model is a dynamic adaptation of the Kralj, Sweetman and AGE-WELL National Innovation Hub - Advancing Policies and Practices in Technology and Aging (APPTA) methodology ^{1 , 2}. Enhancements to the original methodology include the most recent labour force data and the ability to choose between ten alternative population growth scenarios. In the spirit of transparency and open access, the code, data, and the model’s methodology (see User Guide) are available for download on this page. 

For optimal performance, we recommend using this platform on a web browser rather than on a mobile device.