Kolloquium Technische Kybernetik im Wintersemester 2017/18

--- Titel: Disease Dynamics on a Network Game: A Little Empathy Goes a Long Way

Veranstaltungsdatum:  6. Februar 2018 16:00 Uhr

Prof. Ceyhun Eksin
Department of Industrial and Systems Engineering
Texas A&M, USA


Tuesday 2018-02-06 16:00
IST-Seminar-Room 2.255 - Pfaffenwaldring 9 - Campus Stuttgart-Vaihingen




Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals are concerned about contracting a disease from their sick contacts and may utilize protective measures. Sick individuals may be concerned with spreading the disease to their healthy contacts and adopt preemptive measures. Yet, in practice both protective and preemptive changes in behavior come with costs. In this talk I will present a stochastic network disease game model that captures the self-interests of individuals during the spread of a susceptible-infected-susceptible (SIS) disease where individuals react to current risk of disease spread, and their reactions together with the current state of the disease stochastically determine the next stage of the disease. We show that there is a critical level of concern, i.e., empathy, by the sick individuals above which disease is eradicated fast. Furthermore, we find that if the network and disease parameters are above the epidemic threshold, the risk averse behavior by the healthy individuals cannot eradicate the disease without the preemptive measures of the sick individuals. This imbalance in the role played by the response of the infected versus the susceptible individuals in disease eradication affords critical policy insights.




Biographical Information


Ceyhun Eksin is an Adjunct Assistant Professor of Industrial and Systems Engineering Department at Texas A&M. He received his Ph.D. in Electrical and Systems Engineering from the University of Pennsylvania in 2015, and was subsequently a Postdoctoral Fellow at the Georgia Institute of Technology affiliated with both the School of Electrical & Computer Engineering and the School of Biological Sciences. His research interests are in the areas of distributed optimization, game theory and control theory. His current research focuses on game theoretic modeling and optimization of multi-agent systems in biological, communication and energy networks.