Modeling and Evaluating Intervention Options and Strategies for COVID-19 Containment - Dr. Eva Lee
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➡️ COVID-19 Simulation Summit Playlist: https://www.youtube.com/playlist?list=PLAJnaovHtaFR5puHCN4W_4o8cgIHdawDb
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Eva Lee Professor and Director of the Center for Operations Research in Medicine and HealthCare at Georgia Institute of Technology, a center established through funds from the National Science Foundation and the Whitaker Foundation. The center focuses on biomedicine, public health, and defense, advancing domains from basic science to translational medical research; intelligent, personalized, quality, and cost-effective delivery; and medical preparedness and protection of critical infrastructures. She is a Distinguished Scholar in Health Systems, Health System Institute at Georgia Tech and Emory University School of Medicine. She previously served as the Senior Health Systems Engineer and Professor for the U.S. Department of Veterans Affairs. She has also served as Co-Director for ten years for the Center for Health Organization Transformation, an NSF Industry/University Cooperative Research Center.
"SARs, bird flu, H1N1, Ebola crisis in W. Africa, Zika and current SARS-CoV-2 underscore the critical importance of emergency response and medical preparedness. Such needs are wide-spread as globalization and air transportation facilitate rapid disease spread across the world. Computational modeling of infectious disease outbreaks and epidemics offer insights in propagation patterns and facilitate policy makers to synthesize potential interventions. Current models include inclined decay with an exponential adjustment, SEIR (susceptible, exposed, infectious, recovered) compartmental model, discrete time stochastic processes, and transmission tree. While many of these models incorporate contact tracing to predict spread pattern, key elements on optimal usage of scarce resources and effective and efficient process performance (e.g., diagnostics and screening, non-pharmaceutical interventions, trained personnel/robots for treatment, decontamination) have not been included. This is particularly critical in the fight of COVID-19 containment due to lack of testing kits and the prevalence of asymptomatic transmission, and the long period of hospitalization required by severely sick patients.
This work focuses on designing a system computational decision modeling framework that simultaneously i) captures disease spread characteristics, ii) incorporates day-to-day hospital and homecare processes and resource usage, iii) explores non-pharmaceutical intervention, social and human behavior and iv) allows for system optimization to minimize infection and mortality under time and labor constraints."
On April 30th, 2020, the DAIA Foundation has organized an online COVID-19 Simulation Summit. The summit was focused on the use of agent based simulation models for more effective simulation of COVID-19 spread and evaluation of COVID-19 policies. Consisting of live video talks, Q&A sessions, and panel discussions, the event gathered together scientists with insight and experience in simulation modeling of complex systems (especially but not only agent based modeling) and complex systems dynamics; along with scientists and physicians with specific insight into COVID-19 and related epidemiological issues.
The agent based simulation paradigm allows a finer-grained sort of modeling, in which a region (or the world as a whole) is modeled as a specific geometry occupied by interacting autonomous agents with a diversity of specific behavior patterns. An in-depth agent based simulation of COVID-19 spreading would allow better-grounded policy choices to be made regarding how to manage, control and cope with the pandemic.
An agent based simulation, like any other model, depends on the underlying assumptions used to structure it. However, the agent based modeling paradigm provides a more flexible approach to evaluating the consequences of various assumptions, and thus exploring their validity.
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