In December 2019 a new coronavirus started spreading in Asia. Not contained, this virus and the COVID-19 disease it led to, engulfed societies around the world. Many communities including those at UBC were affected, with extreme social distancing and self-isolation measures coming into place. During this difficult time our group attempted to apply some of the tools they had developed towards helping combat the COVID-19 pandemic.
Inference in Epidemiological Models
We used PyProb, the tool developed by members of our group, to perform inference in epidemiological models that are used to describe the spread of infectious diseases like COVID-19. In most cases policy analysts have to manually adjust these models or do parameter sweeps. Our aim was to automate the policy exploration process, helping policy analysts come up with more optimal policy recommendations.
To this end, we used both compartmental and agent-based models of physiology to study the spread of COVID-19-like diseases, and the impact that interventions such as school closures might have on the spread of the disease and the healthcare system.
To demonstrate the use of this system, we have developed the Automated Pandemic Response Profiler, a tool which helps users identify suitable interventions to combat COVID-19 in different geographic locations.
PI: Frank Wood (UBC)
Postdoctoral Fellow: Adam Scibior
Students: Andrew Warrington – Boyan Beronov – Christian Weillbach – Saeid Naderiparizi – Vaden Masrani – Will Harvey