Research Webinar, “Deploying a Data-Driven COVID-19 Screening Policy at the Greek Border", by Kimon Drakopoulos, USC Marshall School of Business
Τhe Research Webinar of the School of Information Sciences and Technology, AUEB, includes distinguished speakers lectures. The third lecture will be given on Monday, December 7, 2020, 14:00, via MS Teams (http://tiny.cc/sist3rdRS ) by Kimon Drakopoulos, Assistant Professor of Data Sciences and Operations, Marshall School of Business, University of Southern California.
In collaboration with the Greek government, we designed and deployed a nation-wide COVID-19 screening protocol for travelers to Greece. The goals of the protocol were to combine limited demographic information about arriving travelers with screening results from recently tested travelers to judiciously allocate Greece's limited testing budget to identify asymptomatic, infected travelers and quickly identify hotspots and spikes in other nations to inform immigration/border policies in real-time.
This talk details the operations of our designed system (including border screening, database management, closed-loop feedback, and liasing with contact-tracing teams) a novel, batched, contextual bandit algorithm tailored to the unique features of this problem and an empirical assessment of the benefits of the deployed system from the summer/fall 2020, showing that targeted testing based on traveler's features essentially doubles the effectiveness compared to random testing and static greylisting. That is, in a country with daily budget of 7500 tests, targeting is as effective as Radom sampling with 14,850 tests, a number that at the time was effectively the testing capacity of the whole country.
Kimon Drakopoulos is an Assistant Professor of Data Sciences and Operations at USC Marshall School of Business, where he researches complex networked systems, information design and information economics. He completed his Ph.D. in the Laboratory for Information and Decision Systems at MIT, focusing on the analysis and control of contagion within networks. His current research revolves around controlling contagion, epidemic or informational as well as the use of information as a lever to improve operational outcomes in the context of testing allocation, fake news propagation and belief polarization.