Grant: Alliance Grants

This proposed work develops technology that can ultimately support public health by drawing on the opportunities inherent in machine learning and modeling. Specifically, this work proposes to develop algorithms that can support the ability to track individuals during COVID-19, future pandemics, and other states of emergency. These algorithms will not function independently like a smartphone app. Instead, it will be designed to work within a larger software platform that can leverage data from multiple sources (telecommunication service providers, social media apps, financial data) and demonstrate the trajectories of both individuals and groups on fine (neighbourhood) and coarse (regional) scales in disease spread and mitigation models. When public health tools such as quarantine, isolation, and physical distancing measures are applied, the algorithms could support efforts to identify and isolate infected individuals as early as possible, carry out comprehensive contact tracing of known infected individuals, and visualize mobility patterns in communities to assess the most effective community-based strategies to minimize infection transmission (e.g. various levels of 'lockdown' and easing of restrictions/return to 'normal'). Our partner, Sightline Innovation (SI), is a Canadian AI company. SI has developed a data trust platform that provides a governance structure around enterprise use of applied machine learning. The proposed work will provide SI with an opportunity to evaluate the capability of their data trust platform, specifically evaluating additional capacities that the project offers to their existing technology-assisted disease modeling and contact tracing applications toward the COVID-19 and future pandemics. The algorithms that result from this project will ultimately be made available to any entity with interests in incorporating mobility data for disease spread and mitigation modeling.