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2026
Conference Paper
Title
From Simulation to Insight: A Human-Centred Interface for Visualizing and Comparing Pandemic Intervention Scenarios
Abstract
This paper presents an interactive visualization system for exploring and comparing the spatio-temporal dynamics of pandemic scenarios. Understanding the potential course of a pandemic is crucial for evidence-based policymaking and to allow the public to understand the likely developments and consequences of policy interventions [15]. However, the outputs of epidemiological simulations, particularly when covering multiple scenarios and interventions, are often complex and difficult to interpret. Our approach addresses this challenge by integrating a spatially explicit epidemiological model with a tangible map-based visualization environment [5].
The system is based on an extended spatial SEIR model at the level of German districts [11]. It incorporates ICU occupancy rates and key interventions such as lockdowns and allows parametrization of infection dynamics over time and space. Model outputs are visualized on a digital map table [6] as colour-coded districts, where colour encodes incidence rates across time. The decreasing reliability of long-term predictions is communicated through confidence intervals provided in the metadata, as well as through temporal changes in the visualization [14]. Users can interactively navigate along the temporal axis to inspect past developments and future projections.
Beyond passive viewing, the system supports active exploration and scenario construction [17]. Users can set initial outbreak locations, adjust model parameters, and directly configure interventions at specific points in time. Multiple scenarios can be created by varying starting conditions, intervention strategies, or model assumptions. These scenarios are organized in separate layers that can be visualized in parallel, or compared along the timeline to support detailed comparative reasoning [7].
By combining spatial simulation, interactive visualization, and scenario comparison on a tangible interface, the proposed system is designed to support and enhance human-centred exploration of complex epidemiological models. It offers policymakers and other stakeholders an accessible tool to better understand potential pandemic trajectories, evaluate intervention strategies, and communicate insights to the public.
The system is based on an extended spatial SEIR model at the level of German districts [11]. It incorporates ICU occupancy rates and key interventions such as lockdowns and allows parametrization of infection dynamics over time and space. Model outputs are visualized on a digital map table [6] as colour-coded districts, where colour encodes incidence rates across time. The decreasing reliability of long-term predictions is communicated through confidence intervals provided in the metadata, as well as through temporal changes in the visualization [14]. Users can interactively navigate along the temporal axis to inspect past developments and future projections.
Beyond passive viewing, the system supports active exploration and scenario construction [17]. Users can set initial outbreak locations, adjust model parameters, and directly configure interventions at specific points in time. Multiple scenarios can be created by varying starting conditions, intervention strategies, or model assumptions. These scenarios are organized in separate layers that can be visualized in parallel, or compared along the timeline to support detailed comparative reasoning [7].
By combining spatial simulation, interactive visualization, and scenario comparison on a tangible interface, the proposed system is designed to support and enhance human-centred exploration of complex epidemiological models. It offers policymakers and other stakeholders an accessible tool to better understand potential pandemic trajectories, evaluate intervention strategies, and communicate insights to the public.