Visual Analytics of Contact Tracing Policy Simulations During an Emergency Response

Epidemiologists use individual-based models to (a) simulate disease spread over dynamic contact networks and (b) investigate strategies control the outbreak. These model simulations generate complex ‘infection maps’ of time-varying transmission trees patterns spread. Conventional statistical analysis outputs offers only limited interpretation. This paper presents a novel visual analytics approach for inspection infection maps along with their associated metadata, developed collaboratively 16 months in an evolving emergency response situation. We introduce concept representative that summarize many components map while preserving epidemiological characteristics each individual tree. also present interactive visualization techniques quick assessment different policies. Through series case studies qualitative evaluation by epidemiologists, we demonstrate how our visualizations can help improve development interpret patterns.