Cheap But Effective: Instituting Effective Pandemic Policies Without Knowing Who’s Infected
Chris Rackauckas
MIT Applied Mathematics Instructor

One way to find out how many people are infected is to figure out who’s infected, but that’s working too hard! In this talk we will look into cheaper alternatives for effective real-time policy making. To this end we introduce SafeBlues, a project that simulates fake virus strands over Bluetooth and utilizes deep neural networks mixed within differential equations to accurately approximate infection statistics weeks before updated statistics are available. We then introduce COEXIST, a quarantine policy which utilizes inexpensive “useless” tests to perform accurate regional case isolation. This work is all being done as part of the Microsoft Pandemic Modeling Project, where the Julia SciML tooling has accelerated the COEXIST simulations by 36,000x and quantitative systems pharmacology simulations for Pfizer by 175x in support of the efforts against COVID-19.