Integration of analytical COVID‑19 models for remote execution and advanced visualization for improved decision making

Wainer, Gabriel | $50,000

Ontario Carleton University 2020 NSERC Alliance COVID-19 Grant

In recent years, simulation models based on the traditional Susceptible-Infectious-Recovered (SIR) equations have been used to predict the pandemic dynamics. These models are being used at present to predict the spread of the disease in most countries worldwide. Studies of COVID‑19 are based on theoretical methods for infectious disease dynamics, which are based on mathematical models that show how the disease spreads. The original model has been used since 1927, and it classifies the individuals involved in the transmission of the disease into those that are Susceptible to the virus, those who are Infectious and finally those who Recovered. The SIR model was extended and adapted numerous times to study the progression of other diseases and advanced new techniques. The Centre for Operational Research and Analysis (CORA) at Defence Research and Development Canada (DRDC, an Agency of the Department of National Defence, DND) has developed several models based; however, these models are not enough to answer all the questions posed by the DND decision-makers. The Advanced Real-Time Simulation laboratory at Carleton University is partnering with CORA to collaborate to study how to adapt the analytical models available so they could be mixed with advanced Geographical Information Systems (GIS), and to be easily modified and adapted when new research results become available, and to be available for easy remote execution.

With funding from the Government of Canada

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