Grant: Alliance Grants

In recent years, we defined new methods for modeling and simulation, and used them to build models based on the traditional Susceptible-Infected-Recovered (SIR) equations (that are being used worldwide to predict the pandemic dynamics). We also have gained experience on integrating simulations and complex spatial visualization engines to allow decision makers to study how the virus spreads. SOLACE is interested on integrating their message broker platform with mathematical models, sensors, GIS and user devices to provide real time COVID-19 information to the population to inform their behavior. Social media platforms has shown to be help in circulating information to large numbers of individuals, and during the current COVID-19 pandemics, government agencies, hospitals and news agencies have made use of these methods to give detailed information on the fly. The use a message broker platform like the one built by SOLACE has potential for this purpose. This research will focus on extending the models study how viruses spread indoors, combining them with SOLACE's broker. We will use detailed 3D models of the buildings on University campuses and adaptations of the SIR model for indoor environments. We will also study how the virus expands in larger areas. We will combine the models and their simulations with Geographical Information Systems and Carleton's Digital Campus map to build spatial versions of the SIR model with adaptations and improvements. The models will be available through the web for remote collaboration and for use of decision makers, and will give real-time information to campus occupants using SOLACE's middleware. This tool will permit studying different strategies for returning to campus at the end of the pandemic, providing insight on the fly to individuals to make informed decisions and help containing the virus during future outbreaks,