Alexander "Sasha" Gutfraind
Master's from Applied Math UWaterloo, PhD from Cornell
Lecturer - Loyola University Medical Center
Adjunct R. A. Professor - U of Illinois at Chicago
Chief Health Data Scientist, Uptake Technologies
Mathematical emergencies : Dynamic and Network-based Methods in Infectious Disease Epidemiology
For over a century, dynamical systems have been an indispensable tool in infectious disease epidemiology. Currently, dynamical systems are being routinely used by policymakers in planning disease monitoring and interventions across the globe. There is also increased attention on applying network analysis tools as a paradigm and for informing dynamical systems models. In my talk, I will illustrate these trends with recent work completed during the peak of the 2014-2015 Ebola outbreak in West Africa. Using an ODE model, we showed that transfusion intervention could be effective in reducing mortality from Ebola, and the best way of implementing this. I will then discuss the use of network data in modeling outbreaks and a recently-introduced method to compensate for gaps in network datasets. The method, which was inspired by multigrid methods for solving large-scale partial differential equations, could be used to synthesize large scale network data as used for disease forecasting. I will argue that mathematical epidemiology will continue growing in importance as a field and as tool for advancing public health.