Consequences of Social Network Structure for Epidemic Interventions
Visiting speaker
Abbas K. Rizi
Doctoral Researcher, Aalto University (Finland)
Past Talk
Virtual
Tuesday
Nov 14, 2023
Watch video
10:00 am
EST
Virtual
177 Huntington Ave.
11th floor
11th floor
Devon House
58 St Katharine's Way
London E1W 1LP, UK
58 St Katharine's Way
London E1W 1LP, UK
The COVID-19 pandemic has revealed gaps in our understanding of epidemic dynamics and the shortcomings of traditional models in real-world scenarios, particularly in comprehending herd immunity. This presentation will focus on how the structure of contact networks affects disease spread and intervention effectiveness. I will highlight the impact of pharmaceutical interventions like vaccination and non-pharmaceutical measures such as contact tracing on epidemic trajectories, considering factors like behavior-based homophily, group structures, spatial characteristics, and heterogeneities of contact networks. Additionally, I will introduce an advanced theoretical framework for analyzing temporal dynamics in networks, which is crucial for understanding disease spread, information dissemination, and public transport system accessibility over time. The presentation will conclude by bridging the concept of temporal network reachability to percolation theory, a significant concept in complex systems studies.
About the speaker
About the speaker
I am a Doctoral Researcher in the Computer Science Department of Aalto University (Finland), specializing in Network Epidemiology. My work revolves around developing and calibrating mathematical and computational models to analyze the effects of various interventions on epidemics. As part of the NordicMath Covid project, I have collaborated with scientists and policymakers of the Nordic countries on COVID-19 strategies. My work also includes linking temporal network theory with non-equilibrium phase transition formalism. My background is in the Physics of Complex Systems, and I enjoy integrating its tools and perspectives with new ideas to solve interdisciplinary problems.
I am a Doctoral Researcher in the Computer Science Department of Aalto University (Finland), specializing in Network Epidemiology. My work revolves around developing and calibrating mathematical and computational models to analyze the effects of various interventions on epidemics. As part of the NordicMath Covid project, I have collaborated with scientists and policymakers of the Nordic countries on COVID-19 strategies. My work also includes linking temporal network theory with non-equilibrium phase transition formalism. My background is in the Physics of Complex Systems, and I enjoy integrating its tools and perspectives with new ideas to solve interdisciplinary problems.
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