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Authors: Lorena Pujante 1 ; Manuel Campos 1 ; 2 ; 3 ; Jose M. Juarez 1 ; 2 ; Bernardo Canovas-Segura 1 and Antonio Morales 1

Affiliations: 1 AIKE, Research Group, Faculty of Computer Science, University of Murcia, Spain ; 2 INTICO Research Institute, Spain ; 3 Murcian Bio-Health Institute (IMIB-Arrixaca), Spain

Keyword(s): Graph Analytics, Graph Database, Epidemiology, Infection Surveillance.

Abstract: Some of epidemiologists’ efforts in dealing with multi-resistant bacterial infections acquired in healthcare settings focus on tracing patient’s activities, carrying out a contact analysis, and identifying the main risk factors that lead the appearance of these infections. Most contact analysis studies assume information is stored in conventional relational databases. To date, little attention has been paid to other storage paradigms. This paper explores the potential of graph databases to establish the complex relations required to compute contact analysis. We discuss the advances in modelling of the temporal and the spatial information of the Electronic Health Record that has to be introduced in the graph database. In this position paper we propose three points for discussion: advances in formal modelling, specific algorithms for graph analysis, and visualisation tools.

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Paper citation in several formats:
Pujante, L.; Campos, M.; Juarez, J.; Canovas-Segura, B. and Morales, A. (2021). Multi-resistant Bacterial Infection Surveillance using a Graph Database with Spatio-temporal Information. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - HEALTHINF; ISBN 978-989-758-490-9; ISSN 2184-4305, SciTePress, pages 741-746. DOI: 10.5220/0010387207410746

@conference{healthinf21,
author={Lorena Pujante. and Manuel Campos. and Jose M. Juarez. and Bernardo Canovas{-}Segura. and Antonio Morales.},
title={Multi-resistant Bacterial Infection Surveillance using a Graph Database with Spatio-temporal Information},
booktitle={Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - HEALTHINF},
year={2021},
pages={741-746},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010387207410746},
isbn={978-989-758-490-9},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - HEALTHINF
TI - Multi-resistant Bacterial Infection Surveillance using a Graph Database with Spatio-temporal Information
SN - 978-989-758-490-9
IS - 2184-4305
AU - Pujante, L.
AU - Campos, M.
AU - Juarez, J.
AU - Canovas-Segura, B.
AU - Morales, A.
PY - 2021
SP - 741
EP - 746
DO - 10.5220/0010387207410746
PB - SciTePress

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