Blue Dot Application

The main objective of this research project is to contribute to developing a model that can provide robust early warning to changes in influenza cases and help to reduce ILI spread globally. The model, Modified Exponential Growth Algorithm (MEGA), will characterize the early ascending phase of epidemic disease and will be used to detect changes in calculated exponential growth parameters that occur over a complete time series of influenza case data. What makes this model unique is that it will detect not only the start and peak of ILI activity, but also when its season ends. Understanding and identifying when it is ILI season is especially important with recent departures of seasonal influenza trends post-Covid-19 pandemic.

An intern who brings skills and knowledge in public health and epidemiology is needed to support the technology team members who don’t have that specific expertise. Because BlueDot is a social enterprise and limited in resources, we need to better optimize our budget while we are commercializing new technology. Hence, support from Mitacs would accelerate this project. This is an opportunity for a student to apply their knowledge in a real world and technology-driven setting.

Faculty Supervisor:

Susan Bondy

Student:

Partner:

BlueDot Inc

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology; Professional, scientific and technical services

University:

University of Toronto

Program: