Next week Dr. Derya Demirtas will present her work on Public access defibrillator location under demand and supply uncertainty at the ISyE / CHHS Seminar at Georgia Tech.
Out-of-hospital cardiac arrest (OHCA) is a significant public health issue, and treatment, namely, cardiopulmonary resuscitation (CPR) and defibrillation, is very time sensitive. Public access defibrillation programs, which deploy automated external defibrillators (AEDs) for lay responder use in an emergency, reduce the time to defibrillation and improve survival rates. In the first part of the talk, I will present the models we developed to guide the deployment of AEDs in public settings. Our models generalize the maximal covering location problem and are motivated by real-world views on AED retrieval behavior by lay responders during a cardiac arrest emergency. We formulated three mixed integer nonlinear models and derived either equivalent integer linear reformulations or easily computable bounds. A case study where we apply our modeling framework to data from Toronto, Canada will also be presented. In the second part of the talk, I will talk about an ongoing work on a brand-new location problem where both demand (OHCA) and supply (AED and lay responder) locations are subject to uncertainty. This new problem is inspired by a Dutch civilian response smart phone app which alerts volunteers when an OHCA occurs in the vicinity and directs them to first a nearby AED and then to the victim. I will propose a comprehensive modeling framework which combines spatial data analytics, optimization and geographical information systems (GIS) modeling. This framework is primarily motivated by the AED deployment in the Netherlands but can be extended to various other settings in which demand and supply locations are uncertain, such as emergency planning and humanitarian logistics.