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In Search of Patient Zero: Visual Analytics of Pathogen Transmission Pathways in Hospitals / T. Baumgartl; M. Petzold; M. Wunderlich; M. Hohn; Daniel Archambault; M. Lieser; A. Dalpke; S. Scheithauer; M. Marschollek; V. M. Eichel; N. T. Mutters; Highmed Consortium; T. Von Landesberger

IEEE Transactions on Visualization and Computer Graphics, Volume: 27, Issue: 2, Pages: 711 - 721

Swansea University Author: Daniel, Archambault

Abstract

Pathogen outbreaks (i.e., outbreaks of bacteria and viruses) in hospitals can cause high mortality rates and increase costs for hospitals significantly. An outbreak is generally noticed when the number of infected patients rises above an endemic level or the usual prevalence of a pathogen in a defin...

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Published in: IEEE Transactions on Visualization and Computer Graphics
ISSN: 1077-2626 2160-9306
Published: IEEE Visual Analytics Science and Technology (VAST) Institute of Electrical and Electronics Engineers (IEEE) 2021
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URI: https://cronfa.swan.ac.uk/Record/cronfa55044
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spelling 2021-02-11T16:20:15.4209995 v2 55044 2020-08-21 In Search of Patient Zero: Visual Analytics of Pathogen Transmission Pathways in Hospitals 8fa6987716a22304ef04d3c3d50ef266 0000-0003-4978-8479 Daniel Archambault Daniel Archambault true false 2020-08-21 SCS Pathogen outbreaks (i.e., outbreaks of bacteria and viruses) in hospitals can cause high mortality rates and increase costs for hospitals significantly. An outbreak is generally noticed when the number of infected patients rises above an endemic level or the usual prevalence of a pathogen in a defined population. Reconstructing transmission pathways back to the source of an outbreak -- the patient zero or index patient -- requires the analysis of microbiological data and patient contacts. This is often manually completed by infection control experts. We present a novel visual analytics approach to support the analysis of transmission pathways, patient contacts, the progression of the outbreak, and patient timelines during hospitalization. Infection control experts applied our solution to a real outbreak of Klebsiella pneumoniae in a large German hospital. Using our system, our experts were able to scale the analysis of transmission pathways to longer time intervals (i.e., several years of data instead of days) and across a larger number of wards. Also, the system is able to reduce the analysis time from days to hours. In our final study, feedback from twenty-five experts from seven German hospitals provides evidence that our solution brings significant benefits for analyzing outbreaks. Journal Article IEEE Transactions on Visualization and Computer Graphics 27 2 711 721 Institute of Electrical and Electronics Engineers (IEEE) IEEE Visual Analytics Science and Technology (VAST) 1077-2626 2160-9306 1 2 2021 2021-02-01 10.1109/tvcg.2020.3030437 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2021-02-11T16:20:15.4209995 2020-08-21T16:59:23.2282081 College of Science Computer Science T. Baumgartl 1 M. Petzold 2 M. Wunderlich 3 M. Hohn 4 Daniel Archambault 0000-0003-4978-8479 5 M. Lieser 6 A. Dalpke 7 S. Scheithauer 8 M. Marschollek 9 V. M. Eichel 10 N. T. Mutters 11 Highmed Consortium 12 T. Von Landesberger 13 55044__18016__24290c5e0afd476cb8af6f6fdaf88e9e.pdf storyline2020.pdf 2020-08-21T17:05:34.9468509 Output 4667715 application/pdf Accepted Manuscript true true eng
title In Search of Patient Zero: Visual Analytics of Pathogen Transmission Pathways in Hospitals
spellingShingle In Search of Patient Zero: Visual Analytics of Pathogen Transmission Pathways in Hospitals
Daniel, Archambault
title_short In Search of Patient Zero: Visual Analytics of Pathogen Transmission Pathways in Hospitals
title_full In Search of Patient Zero: Visual Analytics of Pathogen Transmission Pathways in Hospitals
title_fullStr In Search of Patient Zero: Visual Analytics of Pathogen Transmission Pathways in Hospitals
title_full_unstemmed In Search of Patient Zero: Visual Analytics of Pathogen Transmission Pathways in Hospitals
title_sort In Search of Patient Zero: Visual Analytics of Pathogen Transmission Pathways in Hospitals
author_id_str_mv 8fa6987716a22304ef04d3c3d50ef266
author_id_fullname_str_mv 8fa6987716a22304ef04d3c3d50ef266_***_Daniel, Archambault
author Daniel, Archambault
author2 T. Baumgartl
M. Petzold
M. Wunderlich
M. Hohn
Daniel Archambault
M. Lieser
A. Dalpke
S. Scheithauer
M. Marschollek
V. M. Eichel
N. T. Mutters
Highmed Consortium
T. Von Landesberger
format Journal article
container_title IEEE Transactions on Visualization and Computer Graphics
container_volume 27
container_issue 2
container_start_page 711
publishDate 2021
institution Swansea University
issn 1077-2626
2160-9306
doi_str_mv 10.1109/tvcg.2020.3030437
publisher Institute of Electrical and Electronics Engineers (IEEE)
college_str College of Science
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hierarchy_top_id collegeofscience
hierarchy_top_title College of Science
hierarchy_parent_id collegeofscience
hierarchy_parent_title College of Science
department_str Computer Science{{{_:::_}}}College of Science{{{_:::_}}}Computer Science
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description Pathogen outbreaks (i.e., outbreaks of bacteria and viruses) in hospitals can cause high mortality rates and increase costs for hospitals significantly. An outbreak is generally noticed when the number of infected patients rises above an endemic level or the usual prevalence of a pathogen in a defined population. Reconstructing transmission pathways back to the source of an outbreak -- the patient zero or index patient -- requires the analysis of microbiological data and patient contacts. This is often manually completed by infection control experts. We present a novel visual analytics approach to support the analysis of transmission pathways, patient contacts, the progression of the outbreak, and patient timelines during hospitalization. Infection control experts applied our solution to a real outbreak of Klebsiella pneumoniae in a large German hospital. Using our system, our experts were able to scale the analysis of transmission pathways to longer time intervals (i.e., several years of data instead of days) and across a larger number of wards. Also, the system is able to reduce the analysis time from days to hours. In our final study, feedback from twenty-five experts from seven German hospitals provides evidence that our solution brings significant benefits for analyzing outbreaks.
published_date 2021-02-01T04:25:59Z
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