Some people can have COVID and shed quite a lot of virus whereas others don't. The typical approach uses the same sorts of models that people use to model epidemic spread. Our approach is similar, except that we model this being explicit about how these virus particles and immune cells are actually moving through space.
How do you model a complex system? Traditionally we would observe how the system is behaving and create equations to mimic this behaviour, but this doesn't work for complex systems. This is because the interactions between agents in a complex system can significantly impact the system's overall behaviour.
In today's episode, Melanie Moses, Professor of Computer Science at the University of New Mexico, will answer this question. She'll introduce us to agent-based models, which are very different to how we traditionally model systems. More specifically, Melanie will explain how she used agent-based models to understand the spread of coronavirus in the lungs.
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This show is produced in collaboration with Wavelength Creative. Visit wavelengthcreative.com for more information.