HAIviz: an interactive dashboard for visualising and integrating healthcare-associated genomic epidemiological data

Author:

Permana Budi123,Harris Patrick N. A.42,Roberts Leah W.53,Cuddihy Thom2,Paterson David L.672,Beatson Scott A.38,Forde Brian M.82ORCID

Affiliation:

1. Herston Infectious Diseases Institute, Metro North Health, Queensland, Australia

2. University of Queensland Centre for Clinical Research, Royal Brisbane and Women’s Hospital, Herston, Queensland, Australia

3. School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, Queensland, Australia

4. Pathology Queensland, Central Laboratory, Royal Brisbane and Women’s Hospital, Herston, Queensland, Australia

5. Centre for Immunology and Infection Control, Queensland University of Technology, Brisbane, Queensland, Australia

6. Infectious Diseases Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

7. ADVANCE-ID, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore

8. Australian Infectious Disease Research Centre, The University of Queensland, St Lucia, Queensland, Australia

Abstract

Existing tools for phylogeographic and epidemiological visualisation primarily provide a macro-geographic view of epidemic and pandemic transmission events but offer little support for detailed investigation of outbreaks in healthcare settings. Here, we present HAIviz, an interactive web-based application designed for integrating and visualising genomic epidemiological information to improve the tracking of healthcare-associated infections (HAIs). HAIviz displays and links the outbreak timeline, building map, phylogenetic tree, patient bed movements, and transmission network on a single interactive dashboard. HAIviz has been developed for bacterial outbreak investigations but can be utilised for general epidemiological investigations focused on built environments for which visualisation to customised maps is required. This paper describes and demonstrates the application of HAIviz for HAI outbreak investigations.

Publisher

Microbiology Society

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