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SC25 Talks at the UMD Booth

SC25 Talks at the UMD Booth

Modeling Interdependent Social and Biological Contagions on Massive Multi-layer Networks

No disease spreads in a vacuum. The progression of any pandemic is necessarily contingent on a wide range of human behaviors, from commute and travel patterns to masking and vaccination. Despite this, most infectious disease models treat behavior as an input parameter rather than a dynamic part of the model. Of the simulations which incorporate changing behaviors into the heart of the simulation, only EpiCast has previously shown itself capable of modeling the interplay between behavior and disease spread in heterogeneous populations larger than about a million individuals. We extend the model implemented in EpiCast to deal with more general socio-technical networks, capable of representing relations between people who may not be physically nearby, allowing fear of the disease to spread both in-person and through such a network. These networks can represent connections formed through social media or maintained over long-distances. We also compare how Epicast-simulated outbreaks unfold across a number of scenarios with different rates of fear spread and dissipation, and show how introducing fear spread through these networks impacts the dynamics of these outbreaks.

Speaker Bio - Joy Kitson

Joy Kitson

Joy Kitson is a Computer Science PhD student in the Parallel Systems and Software Group at UMD, advised by Abhinav Bhatele, and completed her Bachelors degree at the University of Delaware in Computer Science and Applied Mathematics in 2020. She studies how to best harness high performance computing resources to support simulations of infectious disease spread. She was selected as a Department of Energy Computational Science Graduate Fellow in 2021, and has interned at Livermore, Argonne, Oak Ridge, and Los Alamos National Laboratories.