Restrictions like physical distancing, closures of schools and businesses, and self-isolation have been key tools in flattening the COVID-19 curve. These restrictions come however with huge economic, social, and mental costs for individuals, communities, and businesses.
As jurisdictions the world over move to reopen education facilities, businesses, and public spaces, there are no comprehensive sources for data-driven insight that municipalities, provincial health authorities or businesses can use to forecast safe levels of interaction. While these sources exist in isolation, integration is often in short supply, contradictory, or missing altogether, which in turn erodes the confidence of decision-makers.
Moreover, current measures have no built-in feedback on their effectiveness. Given all of the unknowns about the virus, it’s tough to understand which measures will successfully keep the COVID-19 curve flattened and which may prove counterproductive. As Canada works to navigate what is quickly becoming a new reality, valid, reliable, comprehensive, and dynamic data is sorely needed.
Project Looking Glass will build a decision-support platform that uses predictive modelling to analyze policies and determine which can best protect Canadians in the new normal. Using the tool, decision-makers will have the ability to say that policy x will have public health impact y and economic impact z.
Looking Glass is led by Kings Distributed Systems in partnership with Riskthinking.AI, Limestone Analytics, Queen’s University, aiSight, and Distributed Compute Labs. Contributors include CENGN, Server Cloud Canada, Dymond, AMPD, PHEMI Systems, Krate Distributed Information Systems, and multiple municipalities in Ontario, B.C., Newfoundland and Saskatchewan.
Decision-makers and those advising them will, simply by accessing the Looking Glass webpage online, be able to engage with an interactive map of Canada. This map will be broken down by census region (municipality, county, or region) and each of these regions will be linked to demographic, economic, and COVID-19 case report data and analysis that is unique to their region. In addition, anonymized data will enable visualizations of people’s movements between municipalities on this same application.
This web-based solution will let those tasked with making these important decisions input potential actions such as physical distancing measures, closing and re-opening of schools and businesses, widespread testing, and contact tracing. Looking Glass will then forecast through established epidemiological and economic models potential outcomes such as infection rates and economic impact of those proposed policies.
Clear, evidence-based understanding of the impact of decisions made to protect the health of Canadians is needed to inform good policy-making. This project will provide possible benefits and risks based on science-driven modelling to better inform public policy and practice for government and industry as physical distancing measures, re-opening of schools and businesses, and widespread testing are considered, and the country looks toward a return to work and community.
Project Looking Glass will help decision-makers target recovery policies in a way that maximizes positive impact while minimizing health risk, and will do this is in a way that is tailored to the unique circumstances of a particular community. The platform also has the potential to reach far beyond COVID-19 recovery. When fully developed, it could be adapted to test and inform the rollout of public health campaigns for vaccinations, or manage tick-borne diseases, as well as nutrition, education, and climate change initiatives. Looking Glass uses data and computation to enable confident decision-making.
One of the important aspects of Project Looking Glass is how it has brought together a diverse set of players to be able to deliver an innovative, enduring, and much-needed solution. The team includes world class scenario generation and data visualization applications from Riskthinking.AI, leading economic model and insights of Limestone Analytics, cutting-edge epidemiological models from Queen’s University researchers, and supported by a distributed computer infrastructure provided by Kings Distributed Systems. This integration will create a powerful application to bring evidence-based, data-driven policy recommendations to the attention of decision-makers in an intuitive and timely manner.