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Mathematical Modeling, Estimation, and Analysis of Epidemics Spreading on Network​s​

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May 14

Speaker: Philip E. Paré
Presentation material: Pare_KTH Digital Futures (pdf 6.1 MB)
Recorded presentation:

Abstract: Highlighted by the ongoing COVID-19 pandemic, the study of spreading processes is a very important research area, and has been a topic of interest for many years over a wide range of areas, including computer science, mathematical systems, biology, physics, social sciences, and economics. More recently, there has been a resurgence of interest in the study of spreading processes focused on spread over networks, motivated not only by recent devastating outbreaks of infectious diseases, but also the rapid spread of opinions and misinformation over social networks and security threats posed by computer viruses. Up to this point these network-dependent spread models have not been validated by real data.

In this talk, I present and analyze mathematical models for network-dependent spread. I use the analysis to validate a SIS (susceptible-infected-susceptible) model employing John Snow’s classical work on cholera epidemics in London in the 1850’s. Given the demonstrated validity of the model, I discuss several control strategies for mitigating spread, and formulate a tractable antidote administration problem that significantly reduces spread. Then I present an SIR (susceptible-infected-recovered) model and illustrate how it can capture the behavior of the 1854 London cholera outbreak and discuss how they are being used for COVID-19 modeling. Finally, I conclude by discussing an ongoing project in collaboration with the Division of Information Science and Engineering​​ on contact tracing where we are developing techniques for infection level estimation using these networked epidemic models and mobile technology.

Bio: Philip E. Paré is a postdoctoral scholar in the Division of Decision and Control Systems in the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology . He received his Ph.D. in Electrical and Computer Engineering (ECE) from the University of Illinois at Urbana-Champaign (UIUC) in 2018. Philip received his B.S. in Mathematics with University Honors and his M.S. in Computer Science from Brigham Young University in 2012 and 2014, respectively. Philip was the recipient of the 2017-2018 Robert T. Chien Memorial Award for excellence in research from the UIUC ECE Department and named a 2017-2018 UIUC College of Engineering Mavis Future Faculty Fellow. His main research topic over the last six years has been modelling, analysis, and control of virus spread over networks, using real data and estimation techniques to validate the models and design implementable mitigation algorithms. Philip is joining Purdue University as an assistant professor in the School of Electrical and Computer Engineering next month.​