Enhancing Canadian Vaccination Strategies Using Machine Learning and Business Analytics

Zhang, Michael | $26,451

Nova Scotia Saint Mary's University 2021 SSHRC

In the proposed research, we intend to address several critical issues all Canadians are facing. Specifically, using a multidisciplinary approach, the proposal aims at understanding Covid-19 immunization urgent issues that need rapid responses. These include: how to allocate vaccines in the presence of supply disruption? How to improve the coordination among different jurisdictions in logistics? Who should be given priority for the vaccine? When and where? How the answers to these questions would/should change during the different stages of the vaccine roll-out lifecycle? Answering these questions provides the required elements for a swift and reflective design, implementation, evaluation, and monitoring of Covid-19 vaccination testing strategies. The team intends to systematically use data to understand related business insights developed through applied analytical disciplines (e.g., statistical, contextual, quantitative, predictive, cognitive) to drive evidence-based decision-making for planning, management, measurement and learning for Covid-19 vaccine roll-out .

The study’s contribution will be a comprehensive investigation of Canadian vaccination strategy using health, economic, social, and ethical perspectives from key informants in business and public communities. The research output can be a useful instructional tool, either by providing understanding of particular groups’ vaccine needs or by providing a set of measurements to evaluate the current vaccine roll-out. This will also contribute to finding solutions to overcome barriers for different populations to access the vaccine.

A second contribution is analysis of data collected and development of an understanding of a range of important factors/variables affecting vaccination outcomes. These may include cost, demand, capacity, scheduling, process management, location, and various resources needed. Machine Learning tools will be utilized for predicting models using real-time data. The findings will support the design and development of Canadian vaccine supply chain in a viable way.

The third contribution will be development of a business analysis framework to examine different alternatives that improve vaccination outcomes for diverse populations. This is one of the key innovative elements in the proposal. Our work will identify inefficiencies in the existing systems and recommend mechanisms to improve them.

With funding from the Government of Canada

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