Visual Analytics for explaining and analysisng contact tracing networks

  • Funded by UK Research and Innovation (UKRI)
  • Total publications:5 publications

Grant number: EP/V033670/1

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2020
    2022
  • Known Financial Commitments (USD)

    $372,886.11
  • Funder

    UK Research and Innovation (UKRI)
  • Principle Investigator

    Pending
  • Research Location

    United Kingdom, Europe
  • Lead Research Institution

    Swansea University
  • Research Category

    Infection prevention and control

  • Research Subcategory

    Restriction measures to prevent secondary transmission in communities

  • Special Interest Tags

    Gender

  • Study Subject

    N/A

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

Contact tracing networks carry invaluable information for researchers to understand the spread of the virus, for policy-makers to control the COVID-19 outbreak, and for the government and the media in informing the public in rich ways. However, current data science tools fall short for the exploratory and explanatory analysis of the temporal, spatial and social aspects of these networks, and little is known on how most effectively the results of such analyses can be communicated broadly. This lack of a toolbox leads to organisations wasting resources on developing partial solutions designed without broad stakeholder engagement. To this end, this project aims to follow a user-centred approach to develop visual analytics methods for the analysis of large collections of contact tracing networks along with techniques for the communication of analysis results in transparent, comprehensive, yet engaging ways. Contact networks come with noteworthy technical and ethical challenges: inherent uncertainties due to the variation in their generation mechanisms, e.g., apps, hospital records, by volunteers; and high volumes of complex and sensitive information represented as event-based interactions with spatio-temporal facets. This project responds to these challenges through two deliverables comprising visualisation methods working simultaneously at group and individual levels while communicating the general trends in the spread: - Visualisations aimed at experts for understanding collections of contact networks to inform public health policies and make in-depth investigations without compromising individuals' privacy. - Visualisations for communicating analysis results with the general public for information and evidencing policy recommendations with representations having a purely explanatory emphasis.

Publicationslinked via Europe PMC

Last Updated:38 minutes ago

View all publications at Europe PMC

Towards explainable community finding.

Visualization for epidemiological modelling: challenges, solutions, reflections and recommendations.

Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach.

In Search of Patient Zero: Visual Analytics of Pathogen Transmission Pathways in Hospitals.

The Effectiveness of Interactive Visualization Techniques for Time Navigation of Dynamic Graphs on Large Displays.