ESID: A Visual Analytics Tool to Epidemiological Emergencies

Visual analysis tools can help illustrate the spread of infectious diseases and enable informed decisions on epidemiology and public health issues. To create visualisation tools that are intuitive, easy to use, and effective in communicating information, continued research and development focusing on user-centric and methodological design models is extremely important. As a contribution to this topic, this paper presents the design and development of the visual analytics application ESID (Epidemiological Scenarios for Infectious Diseases). The goal of ESID is to provide a platform for rapid assessment of the most effective interventions for infectious disease control. ESID provides spatial-temporal analysis, forecasting, comparison of simulations, interactive filters, and accessibility options. In its current form, it shows the simulations of a hybrid graph-equation-based model as introduced in for infection control. The model can be stratified for different age groups and takes into account the properties of the infectious disease as well as human mobility and contact behaviour.Comment: 6 pages, 5 images and 1 table, Eurovis workshop on visual analytics (EuroVA) 202

ESID: Exploring the Design and Development of a Visual Analytics Tool for Epidemiological Emergencies

Visual analytics tools can help illustrate the spread of infectious diseases and enable informed decisions on epidemiological and public health issues. To create visualisation tools that are intuitive, easy to use, and effective in communicating information, continued research and development focusing on user-centric and methodological design models is extremely important. As a contribution to this topic, this paper presents the design and development process of the visual analytics application ESID (Epidemiological Scenarios for Infectious Diseases). ESID is a visual analytics tool aimed at projecting the future developments of infectious disease spread using reported and simulated data based on sound mathematical-epidemiological models. The development process involved a collaborative and participatory design approach with project partners from diverse scientific fields. The findings from these studies, along with the guidelines derived from them, played a pivotal role in shaping the visualisation tool