Crossing the Bubbles: Difference between revisions
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Client: Arley Anderson, [[Ab Initio Software]] <aanderson@abinitio.com> | |||
We are all learning a lot about the dynamics of virus transmission, but often in ways that leaves us having to trust experts who don’t themselves understand why some social settings result in “super-spreading,” others are benign “bubbles”, and how these very different situations interact when people in a city move between them. Your task is to create an intuitive environment that visualises the dynamics of infection and transmission both within and between diverse settings such as schools, private homes, and workplaces. The key challenge is presenting controls that allow people without mathematical training to experiment with causal parameters and understand the often non-linear consequences over time. The visualisations should be delivered via a web browser, intuitively readable by primary school children, but based on real evidence and mathematical models of transmission and infection dynamics. | We are all learning a lot about the dynamics of virus transmission, but often in ways that leaves us having to trust experts who don’t themselves understand why some social settings result in “super-spreading,” others are benign “bubbles”, and how these very different situations interact when people in a city move between them. Your task is to create an intuitive environment that visualises the dynamics of infection and transmission both within and between diverse settings such as schools, private homes, and workplaces. The key challenge is presenting controls that allow people without mathematical training to experiment with causal parameters and understand the often non-linear consequences over time. The visualisations should be delivered via a web browser, intuitively readable by primary school children, but based on real evidence and mathematical models of transmission and infection dynamics. | ||
Revision as of 17:14, 4 November 2020
Client: Arley Anderson, Ab Initio Software <aanderson@abinitio.com>
We are all learning a lot about the dynamics of virus transmission, but often in ways that leaves us having to trust experts who don’t themselves understand why some social settings result in “super-spreading,” others are benign “bubbles”, and how these very different situations interact when people in a city move between them. Your task is to create an intuitive environment that visualises the dynamics of infection and transmission both within and between diverse settings such as schools, private homes, and workplaces. The key challenge is presenting controls that allow people without mathematical training to experiment with causal parameters and understand the often non-linear consequences over time. The visualisations should be delivered via a web browser, intuitively readable by primary school children, but based on real evidence and mathematical models of transmission and infection dynamics.
