Events for June
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WEBINAR SERIES: Digital Technologies for COVID-19
Fri, Jun 12, 2020 @ 11:00 AM - 12:00 PM
USC Viterbi School of Engineering
University Calendar
This week our webinar will feature talks by Dean Yannis Yortsos, Vice Dean Assad Oberai, and Prof. Urbashi Mitra from the USC Viterbi School of Engineering. Please find more details of our speakers and their talks below.
Talk 1: A spatiotemporal SIR model for modeling the spread of an infectious disease - by Yannis Yortsos, Assad Oberai and Harisankar Ramaswamy
Abstract: A continuum model for the spread of an infectious disease is developed by drawing an analogy with the interaction of multiple reacting chemical species. The resulting set of partial differential equations is analyzed and insights are drawn by considering several limiting states. Finally, a simple finite-element scheme is developed to solve these equations and to make predictions corresponding to several what-if scenarios.
Bio: Dr. Yannis Yortsos is the Dean of the USC Viterbi School of Engineering and the Zohrab Kaprielian Chair in Engineering, a position he has held since 2005. He received a BS (Diploma) degree in Chemical Engineering from the National Technical University of Athens, Greece, and MS and PhD degrees from the California Institute of Technology -- all in chemical engineering. His research area is in fluid flow, transport and reaction processes in porous media with specific application to the subsurface. He was elected to the National Academy of Engineering in 2008, where he has also served as Secretary, Vice Chair and Chair of Section 11. Since July 2017, Dr. Yortsos has served as a member of the NAE Council. Along with colleagues at Duke University and Olin College, he co-founded in 2009 the Global Grand Challenges Scholars Program, now adopted by many universities in the U.S. and overseas. He organized and hosted at USC in Fall 2010 the NAE Second Grand Challenges Summit, which spurred in 2013 the Global Grand Challenges Summits. Between 2012 and 2017, Dr. Yortsos was the Chair of the Diversity Committee of the Engineering Deans Council, in which capacity he spearheaded an engineering diversity initiative, now adopted by more than 210 engineering deans nationwide. In recognition of these initiatives, the USC Viterbi School of Engineering received in 2017 the ASEE President's Award, and was one of the four engineering schools nationwide that received the ASEE Award for Excellence in Veterans in Engineering. Dr. Yortsos is the PI of the NSF I-Corps Innovation Node Los Angeles, established in 2014 as a partnership between USC, Caltech and UCLA.
Bio: Assad Oberai is Hughes Professor of Aerospace and Mechanical Engineering and Interim Vice Dean of Research at the USC Viterbi School of Engineering. Prior to joining USC, he was a Professor in the Department of Mechanical Aerospace and Nuclear Engineering at Rensselaer Polytechnic Institute (RPI), the Associate Dean for Research and Graduate Studies in the School of Engineering, and the Associate Director of the Scientific Computation Research Center (SCOREC). Assad was an Assistant Professor of Aerospace and Mechanical Engineering at Boston University from 2001 to 2005, and joined the Rensselaer faculty in 2006. He received a PhD from Stanford University in 1998, an MS from the University of Colorado in 1994, and a Bachelor's degree from Osmania University in 1992, all in Mechanical Engineering. Assad is on the Editorial Board of three journals, including PlosOne.
Talk 2: Group Testing for Efficient SARS-CoV-2 Assessment - by Urbashi Mitra
Abstract: Several challenges to wide-scale virus testing have emerged during the course of the pandemic within the United States. There have been insufficient tests, a lack of key testing elements as well as widely varying accuracies amongst the tests. We review group testing which was introduced in the 1940s by Dorfman, and, more generally, our recent work on active hypothesis testing. Our research focus has been on making decisions with maximized accuracy within a finite amount of time versus minimizing the average stopping time which has been the classical approach. Prior approaches have investigated the asymptotic accuracy of the strategies, whereas we can assess performance for a finite number of observations for our method. We compare and contrast other group testing methods that have been suggested by other research teams. Our numerical results show that one can effectively combine tests of differing accuracies with re-testing to strongly reduce the number of tests needed to test a population. Thoughts on how to extend these ideas to different kinds of testing goals (testing for the virus versus testing for antibodies) will also be provided.
Bio: Urbashi Mitra received the B.S. and the M.S. degrees from the University of California at Berkeley and her Ph.D. from Princeton University. Dr. Mitra is currently the Gordon S. Marshall Professor in Engineering at the University of Southern California. She was the inaugural Editor-in-Chief for the IEEE Transactions on Molecular, Biological and Multi-scale Communications. Dr. Mitra is a Fellow of the IEEE. She is the recipient of: the 2017 IEEE Women in Communications Engineering Technical Achievement Award, a 2015 UK Royal Academy of Engineering Distinguished Visiting Professorship, a 2015 US Fulbright Scholar Award, a 2015-2016 UK Leverhulme Trust Visiting Professorship, IEEE Communications Society Distinguished Lecturer, 2012 Globecom Signal Processing for Communications Symposium Best Paper Award, 2012 US National Academy of Engineering Lillian Gilbreth Lectureship, the 2009 DCOSS Applications & Systems Best Paper Award, Texas Instruments Visiting Professorship (Fall 2002, Rice University), 2001 Okawa Foundation Award, 2000 Ohio State University's College of Engineering Lumley Award for Research, 1997 Ohio State University's College of Engineering MacQuigg Award for Teaching, and a 1996 National Science Foundation CAREER Award. She has been an Associate Editor for multiple IEEE Transactions.
Dr. Mitra has held visiting appointments at: King's College, London, Imperial College, the Delft University of Technology, Stanford University, Rice University, and the Eurecom Institute. Her research interests are in: wireless communications, communication and sensor networks, biological communication systems, detection and estimation and the interface of communication, sensing and control.
Co-hosted by:
Craig Knoblock, Executive Director, USC Information Sciences Institute
Bhaskar Krishnamachari, Director, USC Viterbi Center for CPS and IoTWebCast Link: https://usc.zoom.us/webinar/register/WN_bS2IGZDMTw2aymiLaBAzIw
Audiences: Everyone Is Invited
Contact: Bhaskar Krishnamachari
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WEBINAR SERIES: Digital Technologies for COVID-19
Fri, Jun 19, 2020 @ 11:00 AM - 12:00 PM
USC Viterbi School of Engineering
University Calendar
This week our webinar will feature a talk by Prof. Dave Conti and Dr. Abigail Horn. Prof. Conti is in Division of Biostatistics in the Department of Preventive Medicine and the Norris Comprehensive Cancer Center (NCCC) at USC, and Dr. Horn is a Postdoctoral Fellow in the Department of Preventive Medicine at USC.
Incorporation of risk factors in a stochastic epidemiological COVID-19 model for Los Angeles County -- by Dave Conti & Abigail Horn
Abstract: We have developed an epidemic compartmental model to address the key questions of (1) When and how the epidemic dynamics will impact health care capacity? (2) What happens to the dynamics of the epidemic when social distancing changes? and (3) How will the epidemic affect different at-risk groups? Our model uses stochastic differential equations and approximate Bayes calculation techniques for parameter estimation. We incorporate external information to inform prior distributions for parameter specification. This includes previous studies on risk factors for COVID-19 to inform differences in illness severity (e.g. advanced age, existing health conditions) and the prevalence of these risk factors in Los Angeles County; mobility data to inform time-varying changes in contact rate; and (3) seroprevalence data to estimate the fraction of unobserved illnesses.
Our modeling framework enables modifying parameters at different time points, enabling the specification of interventions, e.g. social distancing scenarios. A key contribution of our model over existing models estimating hospital resource demand is that it accounts for combinations of risk factors (age, unhealthy behaviors, existing comorbidities, and combinations of comorbidities), including area-level differences in prevalence of these risk factors, in model dynamics.
Accounting for differential risk for specific populations allows us to estimate the impact of COVID-19 on these populations in Los Angeles, including analyzing findings by race/ethnicity groups, to inform the prioritization of these populations for protection. For example, this allows us to compare our projections to the observed disparities in death rates across race/ethnicity groups and answer the question of whether these differences can be explained by prevalence of risk factors alone, or if other factors (e.g. disparities in exposure, differences in contact rates) must be involved. We find that death rates are higher for these populations than can be explained by the risk factors alone.
Model-estimated parameters, projections, and probabilities of severe illness for different combinations of risk factors are provided online on our project website: uscbiostats.github.io/COVID19
Bios:
Dave Conti, PhD
Dr. Conti is Professor in the Division of Biostatistics in the Department of Preventive Medicine and the Norris Comprehensive Cancer Center (NCCC) at USC. He is Associate Director for Data Science Integration for the NCCC at USC and the Kenneth T. Norris, Jr. Chair in Cancer Prevention. His research focuses on study design and statistical methods for genetic and environmental epidemiology. His methodological research aims to integrate biological knowledge in statistical modeling and he has several past R01s to develop and investigate the use of Bayesian hierarchical models for genomic studies and to develop statistical methods to integrate genetic and omics data. He has developed statistical and bioinformatics software for analysis, most recently this includes LUCIDus (https://cran.r-project.org/web/packages/LUCIDus/index.html) and hJAM (https://cran.r-project.org/web/packages/hJAM/index.html).
Dr. Conti is currently Director of the Data Science Core for a U19 project investigating aggressive prostate cancer in African-American men integrating the built environment, germline and somatic genetic profiles, gene expression and tumor microenvironment data. He is also Co-Investigator on a P01 focusing on the development of statistical methods for integrated genomics analysis, as well as numerous applied epidemiology studies.
Abigail Horn, PhD
Dr. Horn is a Postdoctoral Fellow in the Department of Preventive Medicine at the University of Southern California and a member of the Center for Applied Network Analysis (CANA). Her research interests involve network epidemiology, probabilistic modeling and data science in the context of public health, with a focus on foodborne diseases and diseases of diet. She received a Ph.D. from the Institute for Data, Systems and Society at MIT and a Bachelor's in Physics from the College of Creative Studies at UCSB.
Prior to joining USC, she led a research project at the German federal-level food protection agency to develop, implement, and evaluate algorithms and decision support systems for modeling food supply networks to identify the source of large-scale outbreaks of foodborne disease. Her work has been funded by the NIH, the Robert Wood Johnson Foundation, the Bayer Foundation, the German Research Foundation, and the Santa Fe Institute.
Co-hosted by:
Craig Knoblock, Executive Director, USC Information Sciences Institute
Bhaskar Krishnamachari, Director, USC Viterbi Center for CPS and IoTWebCast Link: https://usc.zoom.us/webinar/register/WN_bS2IGZDMTw2aymiLaBAzIw
Audiences: Everyone Is Invited
Contact: Bhaskar Krishnamachari
