We welcome you to attend the Vermont Complex Systems speaker series; we are
presenting two distinguished speakers Samuel V. Scarpino, PhD and Alessandro
Vespignani, PhD.
Light refreshments will be served at 11:45am
Samuel V. Scarpino, PhD
Assistant Professor, Mathematics and Statistics,
University of Vermont
Talk begins at 11am
"Predicting infectious disease outbreaks"
Infectious disease outbreaks recapitulate ecology, emerging from the multi-level interaction of hosts, pathogens, and their environment. Therefore, predicting when and where diseases will spread requires a complex systems approach to modeling. In this talk, I will provide an overview of how mathematical epidemiologists use models, statistics, and computer simulations to predict the occurrence and spread of infectious diseases. Specifically, the talk will focus on examples from the recent Ebola virus outbreak, seasonal influenza, and the ongoing Zika virus outbreak. Finally, I will explore exciting future directions and possible fundamental limits to our ability to forecast outbreaks.
Scarpino is a mathematical biologist studying outbreaks as an emergent process and working to improve public health surveillance. His research investigates questions at the intersection of biology, behavior, and disease and his work on surveillance has led to substantive changes in public health practices. Scarpino's highly collaborative research has focused on a broad range of questions outside of disease: from animal movement and group dynamics to the role of genome copy number in evolution.
For more information: http://scarpino.github.io/
Alessandro Vespignani, PhD
Sternberg Distinguished University Professor, Department of Physics
College of Computer and Information Sciences Bouve' College of Health Sciences
Northeastern University
Talk begins at 12pm
"Epidemic modeling does more than forecast”
Recent years have witnessed the development of data driven models of infectious diseases rooted in the combination of large–scale data mining techniques, computational approaches and mathematical modeling. Although these models are increasingly used to support public-health decisions they are often under debate by only considering their value as forecasting tools. Here I will discuss, by using specific modeling examples of the H1N1 pandemic and the West Africa Ebola epidemic, how computational models can be used in real time to provide situational awareness, intervention planning and projections, and the identification of factors that fundamentally influence the course of an outbreak.
Vespignani is known for his work on complex networks, the applications of network theory to the spread of disease and topological properties of the Internet. He has worked in a number of areas of non-equilibrium particle systems, statistical physics and computational sciences, including characterization of non-equilibrium phase transitions, fractal growth and self-organized criticality. Recently his research activity focuses on the interdisciplinary application of statistical and numerical simulation methods in the analysis of epidemic and spreading phenomena and the study of biological, social and technological networks. For several years he has been working on the characterization and modeling of the Internet, the WWW and large-scale information networks. He is now focusing his research activity in modeling the spatial spread of epidemics, including the realistic and data-driven computational modeling of emerging infectious diseases, the resilience of complex networks and the behavior of techno-social systems.
For more information: http://www.mobs-lab.org/alessandro-vespignani.html