Visual analytics based search-analyze-forecast framework for epidemiological time-series data
The COVID-19 pandemic has been a period where time-series of disease statistics, such as the number of cases or vaccinations, have been intensively used by public health professionals to estimate how their region compares to others and estimate what future could look like at home. Conventional visualizations are often limited in terms of advanced comparative features and in supporting forecasting systematically. This paper presents a visual analytics approach to support data-driven prediction based on a search-analyze-predict process comprising a multi-metric, multi-criteria time-series search method and a data-driven prediction technique. These are supported by a visualization framework for the comprehensive comparison of multiple time-series. We inform the design of our approach by getting iterative feedback from public health experts globally, and evaluate it both quantitatively and qualitatively.
Funding
RAMP VIS: Making Visual Analytics an Integral Part of the Technological Infrastructure for Combating COVID-19
UK Research and Innovation
Find out more...History
School
- Science
Department
- Computer Science
Published in
2023 IEEE VIS Workshop on Visualization for Pandemic and Emergency Responses (Vis4PandEmRes)Pages
1 - 7Source
IEEE VIS Workshop on Visualization for Pandemic and Emergency Responses 2023 (Vis4PandEmRes)Publisher
IEEEVersion
- AM (Accepted Manuscript)
Rights holder
© The Institute of Electrical and Electronics Engineers, Inc.Publisher statement
© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Acceptance date
2023-08-01Publication date
2023-12-31Copyright date
2023ISBN
9798350330267Language
- en