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HAIviz: an interactive dashboard for visualising and integrating healthcare-associated genomic epidemiological data.
Permana, Budi; Harris, Patrick N A; Roberts, Leah W; Cuddihy, Thom; Paterson, David L; Beatson, Scott A; Forde, Brian M.
Affiliation
  • Permana B; School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, Queensland, Australia.
  • Harris PNA; University of Queensland Centre for Clinical Research, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.
  • Roberts LW; Herston Infectious Diseases Institute, Metro North Health, Queensland, Australia.
  • Cuddihy T; University of Queensland Centre for Clinical Research, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.
  • Paterson DL; Pathology Queensland, Central Laboratory, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.
  • Beatson SA; School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, Queensland, Australia.
  • Forde BM; Centre for Immunology and Infection Control, Queensland University of Technology, Brisbane, Queensland, Australia.
Microb Genom ; 10(2)2024 Feb.
Article de En | MEDLINE | ID: mdl-38358326
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.
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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Infection croisée / Génomique Type d'étude: Risk_factors_studies Limites: Humans Langue: En Journal: Microb Genom Année: 2024 Type de document: Article Pays d'affiliation: Australie

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Infection croisée / Génomique Type d'étude: Risk_factors_studies Limites: Humans Langue: En Journal: Microb Genom Année: 2024 Type de document: Article Pays d'affiliation: Australie
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