Ulam Lectures 2019—Lauren Ancel Meyers on Preventing the Next Pandemic (Lecture I)
Infectious disease outbreaks often emerge when and where we are least equipped to detect and control them. Over the last few years, public health agencies have raced to prevent the global expansion of Ebola from Africa, Zika from South America, and avian influenza from Asia. Digital disease detection — the use of social media and internet search data to track outbreaks — may buy us life-saving time. Tweets, blogs and Wikipedia hits can reveal what's ailing the world's population more rapidly and at higher geographic resolution than official surveillance systems.
In a series of two lectures, SFI External Professor Lauren Ancel Meyers discusses how network-based mathematical models that leverage such data accelerate the detection and containment of outbreaks.
These two lectures are self-contained and can be enjoyed together or separately.
Reserve your free tickets through the Lensic Box Office online.
Lecture I- Outbreak detection, prediction, and containment in human social networks
Meyers introduces the field of network epidemiology, which applies tools from complex systems science to uncover fundamental drivers of contagion and pressure points for effective control. Infectious diseases spread via encounters between people that can occur in any second of any day in any corner of the globe. By representing the essential structure of human connectivity in a mathematical framework, network epidemiology elucidates hotspots for transmission, early signs of an emerging threat, and ideal strategies for deploying vaccines, antiviral medications and social distancing interventions.
Click here to read about the second lecture, "The Elusive Threat of Influenza"
Lauren Ancel Meyers is the Cooley Professor of Integrative Biology and Statistics and Data Science at The University of Texas at Austin, and a member of the Santa Fe Institute External Faculty. She was trained as a mathematical biologist at Harvard and Stanford Universities and has been a pioneer in the field of network epidemiology and the application of machine learning to improve outbreak detection, forecasting and control. Professor Meyers leads an interdisciplinary team of scientists, engineers, and public health experts in uncovering the social and biological drivers of epidemics and building practical tools for the CDC and other global health agencies to track and mitigate emerging viral threats, including pandemic influenza, Ebola, HIV, and Zika. Her research has been published in over 100 peer-reviewed articles in major journals and covered by the popular press, including The Wall Street Journal, New York Times, Newsweek, Wired and the BBC. Professor Meyers was named as one of the top 100 global innovators under age 35 by the MIT Technology Review in 2004 and received the Joseph Lieberman Award for Significant Contributions to Science in 2017.
About the Ulam Memorial Lecture Series
Many of the most famous books in science, including Relativity by Albert Einstein and QfiD by Richard Feynman, were based on public lectures. The idea behind the series is to have a brilliant scientist deliver a series of public talks on a cutting-edge topic, in honor of the late theoretical mathematician Stanislaw Ulam.
Ulam was a renowned mathematician long associated with Los Alamos National Laboratory who is highly regarded by the Santa Fe Insitute's scientific community. Former SFI Vice President Mike Simmons said, "The enormous range of Ulam's scientific thought encompassed not only mathematics but also physics, computation, biology, and much else. He would have been very much at home in the present-day Santa Fe Institute, which was founded in the year of his death."
These lectures are brought to you at no cost by the Santa Fe Institute, with additional support from The Lensic Performing Arts Center and the Santa Fe Reporter.